id	sid	tid	token	lemma	pos
ijassa-1442	1	1	microsoft	microsoft	PROPN
ijassa-1442	1	2	word	word	NOUN
ijassa-1442	1	3	1442	1442	NUM
ijassa-1442	1	4	-	-	PUNCT
ijassa-1442	1	5	article	article	NOUN
ijassa-1442	1	6	text-6568	text-6568	NOUN
ijassa-1442	1	7	-	-	PUNCT
ijassa-1442	1	8	1	1	NUM
ijassa-1442	1	9	-	-	PUNCT
ijassa-1442	1	10	18	18	NUM
ijassa-1442	1	11	-	-	SYM
ijassa-1442	1	12	20231226	20231226	NUM
ijassa-1442	1	13	adv	adv	PROPN
ijassa-1442	1	14	syst	syst	PROPN
ijassa-1442	1	15	sci	sci	PROPN
ijassa-1442	1	16	appl	appl	PROPN
ijassa-1442	1	17	2023	2023	NUM
ijassa-1442	1	18	;	;	PUNCT
ijassa-1442	1	19	04	04	NUM
ijassa-1442	1	20	;	;	PUNCT
ijassa-1442	1	21	41	41	NUM
ijassa-1442	1	22	-	-	SYM
ijassa-1442	1	23	59	59	NUM
ijassa-1442	1	24	published	publish	VERB
ijassa-1442	1	25	online	online	ADV
ijassa-1442	1	26	at	at	ADP
ijassa-1442	1	27	https://ijassa.ipu.ru	https://ijassa.ipu.ru	ADV
ijassa-1442	1	28	.	.	PUNCT
ijassa-1442	2	1	balancing	balance	VERB
ijassa-1442	2	2	accuracy	accuracy	NOUN
ijassa-1442	2	3	,	,	PUNCT
ijassa-1442	2	4	fairness	fairness	NOUN
ijassa-1442	2	5	and	and	CCONJ
ijassa-1442	2	6	privacy	privacy	NOUN
ijassa-1442	2	7	in	in	ADP
ijassa-1442	2	8	machine	machine	NOUN
ijassa-1442	2	9	learning	learn	VERB
ijassa-1442	2	10	through	through	ADP
ijassa-1442	2	11	adversarial	adversarial	ADJ
ijassa-1442	2	12	learning	learning	NOUN
ijassa-1442	2	13	alexander	alexander	PROPN
ijassa-1442	2	14	eponeshnikov1	eponeshnikov1	PROPN
ijassa-1442	2	15	,	,	PUNCT
ijassa-1442	2	16	rustem	rustem	NOUN
ijassa-1442	2	17	sabitov2	sabitov2	PROPN
ijassa-1442	2	18	,	,	PUNCT
ijassa-1442	2	19	gulnara	gulnara	PROPN
ijassa-1442	2	20	smirnova2	smirnova2	PROPN
ijassa-1442	2	21	*	*	PROPN
ijassa-1442	2	22	,	,	PUNCT
ijassa-1442	2	23	shamil	shamil	PROPN
ijassa-1442	2	24	sabitov1	sabitov1	PROPN
ijassa-1442	2	25	1	1	NUM
ijassa-1442	2	26	kazan	kazan	PROPN
ijassa-1442	2	27	federal	federal	PROPN
ijassa-1442	2	28	university	university	PROPN
ijassa-1442	2	29	,	,	PUNCT
ijassa-1442	2	30	kazan	kazan	PROPN
ijassa-1442	2	31	,	,	PUNCT
ijassa-1442	2	32	russia	russia	PROPN
ijassa-1442	2	33	2	2	NUM
ijassa-1442	2	34	kazan	kazan	PROPN
ijassa-1442	2	35	national	national	PROPN
ijassa-1442	2	36	research	research	PROPN
ijassa-1442	2	37	technical	technical	PROPN
ijassa-1442	2	38	university	university	PROPN
ijassa-1442	2	39	named	name	VERB
ijassa-1442	2	40	after	after	ADP
ijassa-1442	2	41	a.n	a.n	PROPN
ijassa-1442	2	42	.	.	PROPN
ijassa-1442	2	43	tupolev	tupolev	PROPN
ijassa-1442	2	44	–	–	PUNCT
ijassa-1442	2	45	kai	kai	PROPN
ijassa-1442	2	46	,	,	PUNCT
ijassa-1442	2	47	kazan	kazan	PROPN
ijassa-1442	2	48	,	,	PUNCT
ijassa-1442	2	49	russia	russia	PROPN
ijassa-1442	2	50	abstract	abstract	NOUN
ijassa-1442	2	51	:	:	PUNCT
ijassa-1442	2	52	this	this	DET
ijassa-1442	2	53	paper	paper	NOUN
ijassa-1442	2	54	investigates	investigate	VERB
ijassa-1442	2	55	balancing	balance	VERB
ijassa-1442	2	56	accuracy	accuracy	NOUN
ijassa-1442	2	57	,	,	PUNCT
ijassa-1442	2	58	fairness	fairness	NOUN
ijassa-1442	2	59	and	and	CCONJ
ijassa-1442	2	60	privacy	privacy	NOUN
ijassa-1442	2	61	in	in	ADP
ijassa-1442	2	62	machine	machine	NOUN
ijassa-1442	2	63	learning	learn	VERB
ijassa-1442	2	64	through	through	ADP
ijassa-1442	2	65	adversarial	adversarial	ADJ
ijassa-1442	2	66	learning	learning	NOUN
ijassa-1442	2	67	.	.	PUNCT
ijassa-1442	3	1	differential	differential	PROPN
ijassa-1442	3	2	privacy	privacy	NOUN
ijassa-1442	3	3	(	(	PUNCT
ijassa-1442	3	4	dp	dp	NOUN
ijassa-1442	3	5	)	)	PUNCT
ijassa-1442	3	6	provides	provide	VERB
ijassa-1442	3	7	strong	strong	ADJ
ijassa-1442	3	8	guarantees	guarantee	NOUN
ijassa-1442	3	9	for	for	ADP
ijassa-1442	3	10	protecting	protect	VERB
ijassa-1442	3	11	individual	individual	ADJ
ijassa-1442	3	12	privacy	privacy	NOUN
ijassa-1442	3	13	in	in	ADP
ijassa-1442	3	14	datasets	dataset	NOUN
ijassa-1442	3	15	.	.	PUNCT
ijassa-1442	4	1	however	however	ADV
ijassa-1442	4	2	,	,	PUNCT
ijassa-1442	4	3	dp	dp	PROPN
ijassa-1442	4	4	can	can	AUX
ijassa-1442	4	5	impact	impact	VERB
ijassa-1442	4	6	model	model	NOUN
ijassa-1442	4	7	accuracy	accuracy	NOUN
ijassa-1442	4	8	and	and	CCONJ
ijassa-1442	4	9	fairness	fairness	NOUN
ijassa-1442	4	10	of	of	ADP
ijassa-1442	4	11	decisions	decision	NOUN
ijassa-1442	4	12	.	.	PUNCT
ijassa-1442	5	1	this	this	DET
ijassa-1442	5	2	paper	paper	NOUN
ijassa-1442	5	3	explores	explore	VERB
ijassa-1442	5	4	the	the	DET
ijassa-1442	5	5	effect	effect	NOUN
ijassa-1442	5	6	of	of	ADP
ijassa-1442	5	7	integrating	integrate	VERB
ijassa-1442	5	8	dp	dp	NOUN
ijassa-1442	5	9	into	into	ADP
ijassa-1442	5	10	the	the	DET
ijassa-1442	5	11	adversarial	adversarial	ADJ
ijassa-1442	5	12	learning	learning	NOUN
ijassa-1442	5	13	framework	framework	NOUN
ijassa-1442	5	14	called	call	VERB
ijassa-1442	5	15	laftr	laftr	ADV
ijassa-1442	5	16	(	(	PUNCT
ijassa-1442	5	17	learning	learn	VERB
ijassa-1442	5	18	adversarially	adversarially	ADV
ijassa-1442	5	19	fair	fair	ADJ
ijassa-1442	5	20	and	and	CCONJ
ijassa-1442	5	21	transferable	transferable	ADJ
ijassa-1442	5	22	representations	representation	NOUN
ijassa-1442	5	23	)	)	PUNCT
ijassa-1442	5	24	on	on	ADP
ijassa-1442	5	25	fairness	fairness	NOUN
ijassa-1442	5	26	and	and	CCONJ
ijassa-1442	5	27	accuracy	accuracy	NOUN
ijassa-1442	5	28	metrics	metric	NOUN
ijassa-1442	5	29	.	.	PUNCT
ijassa-1442	6	1	experiments	experiment	NOUN
ijassa-1442	6	2	were	be	AUX
ijassa-1442	6	3	conducted	conduct	VERB
ijassa-1442	6	4	using	use	VERB
ijassa-1442	6	5	the	the	DET
ijassa-1442	6	6	adult	adult	NOUN
ijassa-1442	6	7	income	income	NOUN
ijassa-1442	6	8	dataset	dataset	VERB
ijassa-1442	6	9	to	to	PART
ijassa-1442	6	10	classify	classify	VERB
ijassa-1442	6	11	individuals	individual	NOUN
ijassa-1442	6	12	into	into	ADP
ijassa-1442	6	13	high	high	ADJ
ijassa-1442	6	14	vs	vs	ADP
ijassa-1442	6	15	low	low	ADJ
ijassa-1442	6	16	income	income	NOUN
ijassa-1442	6	17	groups	group	NOUN
ijassa-1442	6	18	based	base	VERB
ijassa-1442	6	19	on	on	ADP
ijassa-1442	6	20	features	feature	NOUN
ijassa-1442	6	21	like	like	ADP
ijassa-1442	6	22	age	age	NOUN
ijassa-1442	6	23	,	,	PUNCT
ijassa-1442	6	24	education	education	NOUN
ijassa-1442	6	25	etc	etc	X
ijassa-1442	6	26	.	.	X
ijassa-1442	7	1	gender	gender	NOUN
ijassa-1442	7	2	was	be	AUX
ijassa-1442	7	3	considered	consider	VERB
ijassa-1442	7	4	a	a	DET
ijassa-1442	7	5	sensitive	sensitive	ADJ
ijassa-1442	7	6	attribute	attribute	NOUN
ijassa-1442	7	7	.	.	PUNCT
ijassa-1442	8	1	models	model	NOUN
ijassa-1442	8	2	were	be	AUX
ijassa-1442	8	3	trained	train	VERB
ijassa-1442	8	4	with	with	ADP
ijassa-1442	8	5	different	different	ADJ
ijassa-1442	8	6	levels	level	NOUN
ijassa-1442	8	7	of	of	ADP
ijassa-1442	8	8	dp	dp	NOUN
ijassa-1442	8	9	noise	noise	NOUN
ijassa-1442	8	10	(	(	PUNCT
ijassa-1442	8	11	controlled	control	VERB
ijassa-1442	8	12	by	by	ADP
ijassa-1442	8	13	the	the	DET
ijassa-1442	8	14	epsilon	epsilon	PROPN
ijassa-1442	8	15	hyperparameter	hyperparameter	PROPN
ijassa-1442	8	16	)	)	PUNCT
ijassa-1442	8	17	added	add	VERB
ijassa-1442	8	18	to	to	ADP
ijassa-1442	8	19	different	different	ADJ
ijassa-1442	8	20	modules	module	NOUN
ijassa-1442	8	21	like	like	ADP
ijassa-1442	8	22	the	the	DET
ijassa-1442	8	23	encoder	encoder	NOUN
ijassa-1442	8	24	,	,	PUNCT
ijassa-1442	8	25	classifier	classifier	NOUN
ijassa-1442	8	26	and	and	CCONJ
ijassa-1442	8	27	adversary	adversary	NOUN
ijassa-1442	8	28	.	.	PUNCT
ijassa-1442	9	1	results	result	NOUN
ijassa-1442	9	2	show	show	VERB
ijassa-1442	9	3	that	that	SCONJ
ijassa-1442	9	4	adding	add	VERB
ijassa-1442	9	5	dp	dp	NOUN
ijassa-1442	9	6	consistently	consistently	ADV
ijassa-1442	9	7	improves	improve	VERB
ijassa-1442	9	8	fairness	fairness	NOUN
ijassa-1442	9	9	metrics	metric	NOUN
ijassa-1442	9	10	like	like	ADP
ijassa-1442	9	11	demographic	demographic	ADJ
ijassa-1442	9	12	parity	parity	NOUN
ijassa-1442	9	13	and	and	CCONJ
ijassa-1442	9	14	equalized	equalize	VERB
ijassa-1442	9	15	odds	odd	NOUN
ijassa-1442	9	16	by	by	ADP
ijassa-1442	9	17	3	3	NUM
ijassa-1442	9	18	-	-	SYM
ijassa-1442	9	19	5	5	NUM
ijassa-1442	9	20	%	%	NOUN
ijassa-1442	9	21	compared	compare	VERB
ijassa-1442	9	22	to	to	ADP
ijassa-1442	9	23	an	an	DET
ijassa-1442	9	24	unfair	unfair	ADJ
ijassa-1442	9	25	classifier	classifier	NOUN
ijassa-1442	9	26	,	,	PUNCT
ijassa-1442	9	27	albeit	albeit	SCONJ
ijassa-1442	9	28	at	at	ADP
ijassa-1442	9	29	a	a	DET
ijassa-1442	9	30	cost	cost	NOUN
ijassa-1442	9	31	of	of	ADP
ijassa-1442	9	32	1	1	NUM
ijassa-1442	9	33	-	-	SYM
ijassa-1442	9	34	3	3	NUM
ijassa-1442	9	35	%	%	NOUN
ijassa-1442	9	36	reduction	reduction	NOUN
ijassa-1442	9	37	in	in	ADP
ijassa-1442	9	38	accuracy	accuracy	NOUN
ijassa-1442	9	39	.	.	PUNCT
ijassa-1442	10	1	stronger	strong	ADJ
ijassa-1442	10	2	adversary	adversary	NOUN
ijassa-1442	10	3	models	model	NOUN
ijassa-1442	10	4	further	far	ADV
ijassa-1442	10	5	improve	improve	VERB
ijassa-1442	10	6	fairness	fairness	NOUN
ijassa-1442	10	7	but	but	CCONJ
ijassa-1442	10	8	require	require	VERB
ijassa-1442	10	9	careful	careful	ADJ
ijassa-1442	10	10	tuning	tuning	NOUN
ijassa-1442	10	11	to	to	PART
ijassa-1442	10	12	avoid	avoid	VERB
ijassa-1442	10	13	instability	instability	NOUN
ijassa-1442	10	14	during	during	ADP
ijassa-1442	10	15	training	training	NOUN
ijassa-1442	10	16	.	.	PUNCT
ijassa-1442	11	1	overall	overall	ADV
ijassa-1442	11	2	,	,	PUNCT
ijassa-1442	11	3	with	with	ADP
ijassa-1442	11	4	proper	proper	ADJ
ijassa-1442	11	5	configuration	configuration	NOUN
ijassa-1442	11	6	,	,	PUNCT
ijassa-1442	11	7	dp	dp	NOUN
ijassa-1442	11	8	models	model	NOUN
ijassa-1442	11	9	can	can	AUX
ijassa-1442	11	10	achieve	achieve	VERB
ijassa-1442	11	11	high	high	ADJ
ijassa-1442	11	12	fairness	fairness	NOUN
ijassa-1442	11	13	with	with	ADP
ijassa-1442	11	14	minimal	minimal	ADJ
ijassa-1442	11	15	sacrifice	sacrifice	NOUN
ijassa-1442	11	16	of	of	ADP
ijassa-1442	11	17	accuracy	accuracy	NOUN
ijassa-1442	11	18	compared	compare	VERB
ijassa-1442	11	19	to	to	ADP
ijassa-1442	11	20	an	an	DET
ijassa-1442	11	21	unfair	unfair	ADJ
ijassa-1442	11	22	classifier	classifier	NOUN
ijassa-1442	11	23	.	.	PUNCT
ijassa-1442	12	1	the	the	DET
ijassa-1442	12	2	study	study	NOUN
ijassa-1442	12	3	provides	provide	VERB
ijassa-1442	12	4	insights	insight	NOUN
ijassa-1442	12	5	into	into	ADP
ijassa-1442	12	6	balancing	balance	VERB
ijassa-1442	12	7	competing	compete	VERB
ijassa-1442	12	8	objectives	objective	NOUN
ijassa-1442	12	9	of	of	ADP
ijassa-1442	12	10	privacy	privacy	NOUN
ijassa-1442	12	11	,	,	PUNCT
ijassa-1442	12	12	fairness	fairness	NOUN
ijassa-1442	12	13	and	and	CCONJ
ijassa-1442	12	14	accuracy	accuracy	NOUN
ijassa-1442	12	15	in	in	ADP
ijassa-1442	12	16	machine	machine	NOUN
ijassa-1442	12	17	learning	learning	NOUN
ijassa-1442	12	18	models	model	NOUN
ijassa-1442	12	19	.	.	PUNCT
ijassa-1442	13	1	keywords	keyword	NOUN
ijassa-1442	13	2	:	:	PUNCT
ijassa-1442	13	3	machine	machine	NOUN
ijassa-1442	13	4	learning	learning	NOUN
ijassa-1442	13	5	,	,	PUNCT
ijassa-1442	13	6	differential	differential	NOUN
ijassa-1442	13	7	privacy	privacy	NOUN
ijassa-1442	13	8	,	,	PUNCT
ijassa-1442	13	9	adversarial	adversarial	ADJ
ijassa-1442	13	10	learning	learning	NOUN
ijassa-1442	13	11	,	,	PUNCT
ijassa-1442	13	12	fairness	fairness	NOUN
ijassa-1442	13	13	,	,	PUNCT
ijassa-1442	13	14	accuracy	accuracy	NOUN
ijassa-1442	13	15	,	,	PUNCT
ijassa-1442	13	16	privacy	privacy	NOUN
ijassa-1442	13	17	-	-	PUNCT
ijassa-1442	13	18	preserving	preserve	VERB
ijassa-1442	13	19	models	model	NOUN
ijassa-1442	13	20	1	1	NUM
ijassa-1442	13	21	.	.	PUNCT
ijassa-1442	13	22	introduction	introduction	NOUN
ijassa-1442	13	23	in	in	ADP
ijassa-1442	13	24	the	the	DET
ijassa-1442	13	25	modern	modern	ADJ
ijassa-1442	13	26	world	world	NOUN
ijassa-1442	13	27	,	,	PUNCT
ijassa-1442	13	28	a	a	DET
ijassa-1442	13	29	huge	huge	ADJ
ijassa-1442	13	30	number	number	NOUN
ijassa-1442	13	31	of	of	ADP
ijassa-1442	13	32	different	different	ADJ
ijassa-1442	13	33	industries	industry	NOUN
ijassa-1442	13	34	use	use	VERB
ijassa-1442	13	35	machine	machine	NOUN
ijassa-1442	13	36	learning	learn	VERB
ijassa-1442	13	37	to	to	PART
ijassa-1442	13	38	automate	automate	VERB
ijassa-1442	13	39	processes	process	NOUN
ijassa-1442	13	40	such	such	ADJ
ijassa-1442	13	41	as	as	ADP
ijassa-1442	13	42	credit	credit	NOUN
ijassa-1442	13	43	ratings	rating	NOUN
ijassa-1442	13	44	,	,	PUNCT
ijassa-1442	13	45	spam	spam	NOUN
ijassa-1442	13	46	filtering	filtering	NOUN
ijassa-1442	13	47	.	.	PUNCT
ijassa-1442	14	1	machine	machine	NOUN
ijassa-1442	14	2	learning	learning	NOUN
ijassa-1442	14	3	plays	play	VERB
ijassa-1442	14	4	an	an	DET
ijassa-1442	14	5	important	important	ADJ
ijassa-1442	14	6	role	role	NOUN
ijassa-1442	14	7	in	in	ADP
ijassa-1442	14	8	preventing	prevent	VERB
ijassa-1442	14	9	financial	financial	ADJ
ijassa-1442	14	10	losses	loss	NOUN
ijassa-1442	14	11	in	in	ADP
ijassa-1442	14	12	the	the	DET
ijassa-1442	14	13	banking	banking	NOUN
ijassa-1442	14	14	industry	industry	NOUN
ijassa-1442	14	15	.	.	PUNCT
ijassa-1442	15	1	perhaps	perhaps	ADV
ijassa-1442	15	2	the	the	DET
ijassa-1442	15	3	most	most	ADV
ijassa-1442	15	4	urgent	urgent	ADJ
ijassa-1442	15	5	task	task	NOUN
ijassa-1442	15	6	of	of	ADP
ijassa-1442	15	7	forecasting	forecasting	NOUN
ijassa-1442	15	8	is	be	AUX
ijassa-1442	15	9	the	the	DET
ijassa-1442	15	10	assessment	assessment	NOUN
ijassa-1442	15	11	of	of	ADP
ijassa-1442	15	12	credit	credit	NOUN
ijassa-1442	15	13	risk	risk	NOUN
ijassa-1442	15	14	(	(	PUNCT
ijassa-1442	15	15	the	the	DET
ijassa-1442	15	16	risk	risk	NOUN
ijassa-1442	15	17	of	of	ADP
ijassa-1442	15	18	default	default	NOUN
ijassa-1442	15	19	on	on	ADP
ijassa-1442	15	20	debt	debt	NOUN
ijassa-1442	15	21	)	)	PUNCT
ijassa-1442	15	22	.	.	PUNCT
ijassa-1442	16	1	such	such	ADJ
ijassa-1442	16	2	risks	risk	NOUN
ijassa-1442	16	3	can	can	AUX
ijassa-1442	16	4	lead	lead	VERB
ijassa-1442	16	5	to	to	ADP
ijassa-1442	16	6	losses	loss	NOUN
ijassa-1442	16	7	of	of	ADP
ijassa-1442	16	8	billions	billion	NOUN
ijassa-1442	16	9	of	of	ADP
ijassa-1442	16	10	dollars	dollar	NOUN
ijassa-1442	16	11	annually	annually	ADV
ijassa-1442	16	12	.	.	PUNCT
ijassa-1442	17	1	a	a	DET
ijassa-1442	17	2	good	good	ADJ
ijassa-1442	17	3	result	result	NOUN
ijassa-1442	17	4	of	of	ADP
ijassa-1442	17	5	machine	machine	NOUN
ijassa-1442	17	6	learning	learning	NOUN
ijassa-1442	17	7	mainly	mainly	ADV
ijassa-1442	17	8	depends	depend	VERB
ijassa-1442	17	9	on	on	ADP
ijassa-1442	17	10	the	the	DET
ijassa-1442	17	11	huge	huge	ADJ
ijassa-1442	17	12	amount	amount	NOUN
ijassa-1442	17	13	of	of	ADP
ijassa-1442	17	14	data	datum	NOUN
ijassa-1442	17	15	in	in	ADP
ijassa-1442	17	16	which	which	PRON
ijassa-1442	17	17	biases	bias	NOUN
ijassa-1442	17	18	can	can	AUX
ijassa-1442	17	19	be	be	AUX
ijassa-1442	17	20	found	find	VERB
ijassa-1442	17	21	in	in	ADP
ijassa-1442	17	22	favor	favor	NOUN
ijassa-1442	17	23	of	of	ADP
ijassa-1442	17	24	certain	certain	ADJ
ijassa-1442	17	25	attributes	attribute	NOUN
ijassa-1442	17	26	that	that	PRON
ijassa-1442	17	27	are	be	AUX
ijassa-1442	17	28	not	not	PART
ijassa-1442	17	29	fair	fair	ADJ
ijassa-1442	17	30	in	in	ADP
ijassa-1442	17	31	reality	reality	NOUN
ijassa-1442	17	32	[	[	X
ijassa-1442	17	33	8	8	NUM
ijassa-1442	17	34	]	]	PUNCT
ijassa-1442	17	35	.	.	PUNCT
ijassa-1442	18	1	for	for	ADP
ijassa-1442	18	2	example	example	NOUN
ijassa-1442	18	3	,	,	PUNCT
ijassa-1442	18	4	by	by	ADP
ijassa-1442	18	5	learning	learn	VERB
ijassa-1442	18	6	from	from	ADP
ijassa-1442	18	7	unfair	unfair	ADJ
ijassa-1442	18	8	data	datum	NOUN
ijassa-1442	18	9	,	,	PUNCT
ijassa-1442	18	10	a	a	DET
ijassa-1442	18	11	classification	classification	NOUN
ijassa-1442	18	12	model	model	NOUN
ijassa-1442	18	13	of	of	ADP
ijassa-1442	18	14	an	an	DET
ijassa-1442	18	15	automated	automate	VERB
ijassa-1442	18	16	recruitment	recruitment	NOUN
ijassa-1442	18	17	system	system	NOUN
ijassa-1442	18	18	is	be	AUX
ijassa-1442	18	19	more	more	ADV
ijassa-1442	18	20	likely	likely	ADJ
ijassa-1442	18	21	to	to	PART
ijassa-1442	18	22	hire	hire	VERB
ijassa-1442	18	23	candidates	candidate	NOUN
ijassa-1442	18	24	from	from	ADP
ijassa-1442	18	25	certain	certain	ADJ
ijassa-1442	18	26	racial	racial	ADJ
ijassa-1442	18	27	or	or	CCONJ
ijassa-1442	18	28	gender	gender	NOUN
ijassa-1442	18	29	groups	group	NOUN
ijassa-1442	18	30	or	or	CCONJ
ijassa-1442	18	31	to	to	PART
ijassa-1442	18	32	favor	favor	VERB
ijassa-1442	18	33	candidates	candidate	NOUN
ijassa-1442	18	34	of	of	ADP
ijassa-1442	18	35	a	a	DET
ijassa-1442	18	36	certain	certain	ADJ
ijassa-1442	18	37	age	age	NOUN
ijassa-1442	18	38	.	.	PUNCT
ijassa-1442	19	1	algorithmic	algorithmic	ADJ
ijassa-1442	19	2	bias	bias	NOUN
ijassa-1442	19	3	is	be	AUX
ijassa-1442	19	4	a	a	DET
ijassa-1442	19	5	growing	grow	VERB
ijassa-1442	19	6	subject	subject	NOUN
ijassa-1442	19	7	of	of	ADP
ijassa-1442	19	8	much	much	ADJ
ijassa-1442	19	9	discussion	discussion	NOUN
ijassa-1442	19	10	and	and	CCONJ
ijassa-1442	19	11	debate	debate	NOUN
ijassa-1442	19	12	in	in	ADP
ijassa-1442	19	13	the	the	DET
ijassa-1442	19	14	use	use	NOUN
ijassa-1442	19	15	of	of	ADP
ijassa-1442	19	16	ai	ai	NOUN
ijassa-1442	19	17	.	.	PUNCT
ijassa-1442	20	1	this	this	PRON
ijassa-1442	20	2	is	be	AUX
ijassa-1442	20	3	a	a	DET
ijassa-1442	20	4	complex	complex	ADJ
ijassa-1442	20	5	topic	topic	NOUN
ijassa-1442	20	6	due	due	ADP
ijassa-1442	20	7	to	to	ADP
ijassa-1442	20	8	the	the	DET
ijassa-1442	20	9	potential	potential	ADJ
ijassa-1442	20	10	complexity	complexity	NOUN
ijassa-1442	20	11	of	of	ADP
ijassa-1442	20	12	the	the	DET
ijassa-1442	20	13	mathematical	mathematical	ADJ
ijassa-1442	20	14	definition	definition	NOUN
ijassa-1442	20	15	of	of	ADP
ijassa-1442	20	16	what	what	PRON
ijassa-1442	20	17	it	it	PRON
ijassa-1442	20	18	means	mean	VERB
ijassa-1442	20	19	to	to	PART
ijassa-1442	20	20	be	be	AUX
ijassa-1442	20	21	“	"	PUNCT
ijassa-1442	20	22	fair	fair	ADJ
ijassa-1442	20	23	”	"	PUNCT
ijassa-1442	20	24	in	in	ADP
ijassa-1442	20	25	decision	decision	NOUN
ijassa-1442	20	26	making	making	NOUN
ijassa-1442	20	27	.	.	PUNCT
ijassa-1442	21	1	fairness	fairness	NOUN
ijassa-1442	21	2	depends	depend	VERB
ijassa-1442	21	3	on	on	ADP
ijassa-1442	21	4	the	the	DET
ijassa-1442	21	5	situation	situation	NOUN
ijassa-1442	21	6	and	and	CCONJ
ijassa-1442	21	7	is	be	AUX
ijassa-1442	21	8	not	not	PART
ijassa-1442	21	9	only	only	ADV
ijassa-1442	21	10	a	a	DET
ijassa-1442	21	11	reflection	reflection	NOUN
ijassa-1442	21	12	of	of	ADP
ijassa-1442	21	13	values	value	NOUN
ijassa-1442	21	14	,	,	PUNCT
ijassa-1442	21	15	ethics	ethic	NOUN
ijassa-1442	21	16	and	and	CCONJ
ijassa-1442	21	17	legal	legal	ADJ
ijassa-1442	21	18	norms	norm	NOUN
ijassa-1442	21	19	.	.	PUNCT
ijassa-1442	22	1	however	however	ADV
ijassa-1442	22	2	,	,	PUNCT
ijassa-1442	22	3	there	there	PRON
ijassa-1442	22	4	are	be	VERB
ijassa-1442	22	5	clear	clear	ADJ
ijassa-1442	22	6	ways	way	NOUN
ijassa-1442	22	7	to	to	PART
ijassa-1442	22	8	approach	approach	VERB
ijassa-1442	22	9	ai	ai	VERB
ijassa-1442	22	10	fairness	fairness	NOUN
ijassa-1442	22	11	issues	issue	NOUN
ijassa-1442	22	12	.	.	PUNCT
ijassa-1442	23	1	quite	quite	ADV
ijassa-1442	23	2	often	often	ADV
ijassa-1442	23	3	,	,	PUNCT
ijassa-1442	23	4	individual	individual	ADJ
ijassa-1442	23	5	and	and	CCONJ
ijassa-1442	23	6	sensitive	sensitive	ADJ
ijassa-1442	23	7	data	datum	NOUN
ijassa-1442	23	8	(	(	PUNCT
ijassa-1442	23	9	for	for	ADP
ijassa-1442	23	10	example	example	NOUN
ijassa-1442	23	11	,	,	PUNCT
ijassa-1442	23	12	financial	financial	ADJ
ijassa-1442	23	13	transactions	transaction	NOUN
ijassa-1442	23	14	or	or	CCONJ
ijassa-1442	23	15	tax	tax	NOUN
ijassa-1442	23	16	payments	payment	NOUN
ijassa-1442	23	17	)	)	PUNCT
ijassa-1442	23	18	are	be	AUX
ijassa-1442	23	19	taken	take	VERB
ijassa-1442	23	20	to	to	PART
ijassa-1442	23	21	solve	solve	VERB
ijassa-1442	23	22	machine	machine	NOUN
ijassa-1442	23	23	learning	learning	NOUN
ijassa-1442	23	24	problems	problem	NOUN
ijassa-1442	23	25	.	.	PUNCT
ijassa-1442	24	1	because	because	SCONJ
ijassa-1442	24	2	of	of	ADP
ijassa-1442	24	3	this	this	PRON
ijassa-1442	24	4	,	,	PUNCT
ijassa-1442	24	5	algorithms	algorithm	NOUN
ijassa-1442	24	6	must	must	AUX
ijassa-1442	24	7	*	*	PUNCT
ijassa-1442	24	8	corresponding	correspond	VERB
ijassa-1442	24	9	author	author	NOUN
ijassa-1442	24	10	:	:	PUNCT
ijassa-1442	24	11	seyl@mail.ru	seyl@mail.ru	NOUN
ijassa-1442	24	12	balancing	balance	VERB
ijassa-1442	24	13	accuracy	accuracy	NOUN
ijassa-1442	24	14	,	,	PUNCT
ijassa-1442	24	15	fairness	fairness	NOUN
ijassa-1442	24	16	and	and	CCONJ
ijassa-1442	24	17	privacy	privacy	NOUN
ijassa-1442	24	18	in	in	ADP
ijassa-1442	24	19	machine	machine	NOUN
ijassa-1442	24	20	learning	learning	NOUN
ijassa-1442	24	21	…	…	PUNCT
ijassa-1442	24	22	41	41	NUM
ijassa-1442	24	23	copyright	copyright	NOUN
ijassa-1442	24	24	©	©	PROPN
ijassa-1442	24	25	2023	2023	NUM
ijassa-1442	24	26	assa	assa	NOUN
ijassa-1442	24	27	.	.	PUNCT
ijassa-1442	25	1	adv	adv	PROPN
ijassa-1442	25	2	.	.	PUNCT
ijassa-1442	26	1	in	in	ADP
ijassa-1442	26	2	systems	system	NOUN
ijassa-1442	26	3	science	science	NOUN
ijassa-1442	26	4	and	and	CCONJ
ijassa-1442	26	5	appl	appl	NOUN
ijassa-1442	26	6	.	.	PUNCT
ijassa-1442	27	1	(	(	PUNCT
ijassa-1442	27	2	2023	2023	NUM
ijassa-1442	27	3	)	)	PUNCT
ijassa-1442	27	4	guarantee	guarantee	NOUN
ijassa-1442	27	5	privacy	privacy	NOUN
ijassa-1442	27	6	.	.	PUNCT
ijassa-1442	28	1	one	one	NUM
ijassa-1442	28	2	of	of	ADP
ijassa-1442	28	3	the	the	DET
ijassa-1442	28	4	methods	method	NOUN
ijassa-1442	28	5	is	be	AUX
ijassa-1442	28	6	differential	differential	ADJ
ijassa-1442	28	7	privacy	privacy	NOUN
ijassa-1442	28	8	.	.	PUNCT
ijassa-1442	29	1	differential	differential	PROPN
ijassa-1442	29	2	privacy	privacy	NOUN
ijassa-1442	29	3	(	(	PUNCT
ijassa-1442	29	4	dp	dp	NOUN
ijassa-1442	29	5	)	)	PUNCT
ijassa-1442	29	6	is	be	AUX
ijassa-1442	29	7	a	a	DET
ijassa-1442	29	8	mathematical	mathematical	ADJ
ijassa-1442	29	9	definition	definition	NOUN
ijassa-1442	29	10	of	of	ADP
ijassa-1442	29	11	the	the	DET
ijassa-1442	29	12	loss	loss	NOUN
ijassa-1442	29	13	of	of	ADP
ijassa-1442	29	14	confidential	confidential	ADJ
ijassa-1442	29	15	data	datum	NOUN
ijassa-1442	29	16	of	of	ADP
ijassa-1442	29	17	individuals	individual	NOUN
ijassa-1442	29	18	when	when	SCONJ
ijassa-1442	29	19	their	their	PRON
ijassa-1442	29	20	personal	personal	ADJ
ijassa-1442	29	21	information	information	NOUN
ijassa-1442	29	22	is	be	AUX
ijassa-1442	29	23	used	use	VERB
ijassa-1442	29	24	to	to	PART
ijassa-1442	29	25	create	create	VERB
ijassa-1442	29	26	a	a	DET
ijassa-1442	29	27	product	product	NOUN
ijassa-1442	29	28	.	.	PUNCT
ijassa-1442	30	1	differential	differential	ADJ
ijassa-1442	30	2	privacy	privacy	NOUN
ijassa-1442	30	3	allows	allow	VERB
ijassa-1442	30	4	to	to	PART
ijassa-1442	30	5	find	find	VERB
ijassa-1442	30	6	a	a	DET
ijassa-1442	30	7	balance	balance	NOUN
ijassa-1442	30	8	between	between	ADP
ijassa-1442	30	9	privacy	privacy	NOUN
ijassa-1442	30	10	and	and	CCONJ
ijassa-1442	30	11	accuracy	accuracy	NOUN
ijassa-1442	30	12	using	use	VERB
ijassa-1442	30	13	a	a	DET
ijassa-1442	30	14	positive	positive	ADJ
ijassa-1442	30	15	value	value	NOUN
ijassa-1442	30	16	.	.	PUNCT
ijassa-1442	31	1	if	if	SCONJ
ijassa-1442	31	2	is	be	AUX
ijassa-1442	31	3	small	small	ADJ
ijassa-1442	31	4	,	,	PUNCT
ijassa-1442	31	5	then	then	ADV
ijassa-1442	31	6	we	we	PRON
ijassa-1442	31	7	keep	keep	VERB
ijassa-1442	31	8	more	more	ADJ
ijassa-1442	31	9	privacy	privacy	NOUN
ijassa-1442	31	10	,	,	PUNCT
ijassa-1442	31	11	but	but	CCONJ
ijassa-1442	31	12	we	we	PRON
ijassa-1442	31	13	degrade	degrade	VERB
ijassa-1442	31	14	accuracy	accuracy	NOUN
ijassa-1442	31	15	.	.	PUNCT
ijassa-1442	32	1	if	if	SCONJ
ijassa-1442	32	2	is	be	AUX
ijassa-1442	32	3	big	big	ADJ
ijassa-1442	32	4	,	,	PUNCT
ijassa-1442	32	5	then	then	ADV
ijassa-1442	32	6	privacy	privacy	NOUN
ijassa-1442	32	7	suffers	suffer	VERB
ijassa-1442	32	8	for	for	ADP
ijassa-1442	32	9	the	the	DET
ijassa-1442	32	10	sake	sake	NOUN
ijassa-1442	32	11	of	of	ADP
ijassa-1442	32	12	accuracy	accuracy	NOUN
ijassa-1442	32	13	.	.	PUNCT
ijassa-1442	33	1	meaning	meaning	NOUN
ijassa-1442	33	2	of	of	ADP
ijassa-1442	33	3	varies	varie	NOUN
ijassa-1442	33	4	from	from	ADP
ijassa-1442	33	5	0	0	NUM
ijassa-1442	33	6	to	to	ADP
ijassa-1442	33	7	infinity	infinity	NOUN
ijassa-1442	33	8	.	.	PUNCT
ijassa-1442	34	1	to	to	PART
ijassa-1442	34	2	train	train	VERB
ijassa-1442	34	3	models	model	NOUN
ijassa-1442	34	4	with	with	ADP
ijassa-1442	34	5	dp	dp	NOUN
ijassa-1442	34	6	,	,	PUNCT
ijassa-1442	34	7	use	use	VERB
ijassa-1442	34	8	dp	dp	NOUN
ijassa-1442	34	9	-	-	PUNCT
ijassa-1442	34	10	sgd	sgd	NOUN
ijassa-1442	34	11	.	.	PUNCT
ijassa-1442	35	1	the	the	DET
ijassa-1442	35	2	core	core	NOUN
ijassa-1442	35	3	idea	idea	NOUN
ijassa-1442	35	4	is	be	AUX
ijassa-1442	35	5	that	that	SCONJ
ijassa-1442	35	6	training	train	VERB
ijassa-1442	35	7	a	a	DET
ijassa-1442	35	8	model	model	NOUN
ijassa-1442	35	9	can	can	AUX
ijassa-1442	35	10	be	be	AUX
ijassa-1442	35	11	done	do	VERB
ijassa-1442	35	12	through	through	ADP
ijassa-1442	35	13	access	access	NOUN
ijassa-1442	35	14	to	to	ADP
ijassa-1442	35	15	its	its	PRON
ijassa-1442	35	16	parameter	parameter	NOUN
ijassa-1442	35	17	gradients	gradient	NOUN
ijassa-1442	35	18	,	,	PUNCT
ijassa-1442	35	19	i.e.	i.e.	X
ijassa-1442	35	20	,	,	PUNCT
ijassa-1442	35	21	the	the	DET
ijassa-1442	35	22	gradients	gradient	NOUN
ijassa-1442	35	23	of	of	ADP
ijassa-1442	35	24	the	the	DET
ijassa-1442	35	25	loss	loss	NOUN
ijassa-1442	35	26	with	with	ADP
ijassa-1442	35	27	respect	respect	NOUN
ijassa-1442	35	28	to	to	ADP
ijassa-1442	35	29	each	each	DET
ijassa-1442	35	30	parameter	parameter	NOUN
ijassa-1442	35	31	of	of	ADP
ijassa-1442	35	32	your	your	PRON
ijassa-1442	35	33	model	model	NOUN
ijassa-1442	35	34	.	.	PUNCT
ijassa-1442	36	1	if	if	SCONJ
ijassa-1442	36	2	this	this	DET
ijassa-1442	36	3	access	access	NOUN
ijassa-1442	36	4	preserves	preserve	VERB
ijassa-1442	36	5	differential	differential	ADJ
ijassa-1442	36	6	privacy	privacy	NOUN
ijassa-1442	36	7	of	of	ADP
ijassa-1442	36	8	the	the	DET
ijassa-1442	36	9	training	training	NOUN
ijassa-1442	36	10	data	datum	NOUN
ijassa-1442	36	11	,	,	PUNCT
ijassa-1442	36	12	so	so	ADV
ijassa-1442	36	13	does	do	VERB
ijassa-1442	36	14	the	the	DET
ijassa-1442	36	15	resulting	result	VERB
ijassa-1442	36	16	model	model	NOUN
ijassa-1442	36	17	,	,	PUNCT
ijassa-1442	36	18	per	per	ADP
ijassa-1442	36	19	the	the	DET
ijassa-1442	36	20	post	post	ADJ
ijassa-1442	36	21	-	-	ADJ
ijassa-1442	36	22	processing	processing	ADJ
ijassa-1442	36	23	property	property	NOUN
ijassa-1442	36	24	of	of	ADP
ijassa-1442	36	25	differential	differential	ADJ
ijassa-1442	36	26	privacy	privacy	NOUN
ijassa-1442	36	27	.	.	PUNCT
ijassa-1442	37	1	summarizing	summarize	VERB
ijassa-1442	37	2	all	all	PRON
ijassa-1442	37	3	of	of	ADP
ijassa-1442	37	4	the	the	DET
ijassa-1442	37	5	above	above	ADJ
ijassa-1442	37	6	,	,	PUNCT
ijassa-1442	37	7	machine	machine	NOUN
ijassa-1442	37	8	learning	learning	NOUN
ijassa-1442	37	9	models	model	NOUN
ijassa-1442	37	10	must	must	AUX
ijassa-1442	37	11	guarantee	guarantee	VERB
ijassa-1442	37	12	data	datum	NOUN
ijassa-1442	37	13	privacy	privacy	NOUN
ijassa-1442	37	14	while	while	SCONJ
ijassa-1442	37	15	avoiding	avoid	VERB
ijassa-1442	37	16	discrimination	discrimination	NOUN
ijassa-1442	37	17	and	and	CCONJ
ijassa-1442	37	18	ensuring	ensure	VERB
ijassa-1442	37	19	fair	fair	ADJ
ijassa-1442	37	20	decision	decision	NOUN
ijassa-1442	37	21	-	-	PUNCT
ijassa-1442	37	22	making	making	NOUN
ijassa-1442	37	23	.	.	PUNCT
ijassa-1442	38	1	however	however	ADV
ijassa-1442	38	2	,	,	PUNCT
ijassa-1442	38	3	the	the	DET
ijassa-1442	38	4	use	use	NOUN
ijassa-1442	38	5	of	of	ADP
ijassa-1442	38	6	these	these	DET
ijassa-1442	38	7	methods	method	NOUN
ijassa-1442	38	8	may	may	AUX
ijassa-1442	38	9	have	have	VERB
ijassa-1442	38	10	an	an	DET
ijassa-1442	38	11	impact	impact	NOUN
ijassa-1442	38	12	on	on	ADP
ijassa-1442	38	13	the	the	DET
ijassa-1442	38	14	accuracy	accuracy	NOUN
ijassa-1442	38	15	of	of	ADP
ijassa-1442	38	16	the	the	DET
ijassa-1442	38	17	model	model	NOUN
ijassa-1442	38	18	.	.	PUNCT
ijassa-1442	39	1	the	the	DET
ijassa-1442	39	2	research	research	NOUN
ijassa-1442	39	3	questions	question	NOUN
ijassa-1442	39	4	below	below	ADV
ijassa-1442	39	5	in	in	ADP
ijassa-1442	39	6	this	this	DET
ijassa-1442	39	7	work	work	NOUN
ijassa-1442	39	8	aim	aim	VERB
ijassa-1442	39	9	to	to	PART
ijassa-1442	39	10	examine	examine	VERB
ijassa-1442	39	11	the	the	DET
ijassa-1442	39	12	impact	impact	NOUN
ijassa-1442	39	13	of	of	ADP
ijassa-1442	39	14	privacy	privacy	NOUN
ijassa-1442	39	15	on	on	ADP
ijassa-1442	39	16	fairness	fairness	NOUN
ijassa-1442	39	17	and	and	CCONJ
ijassa-1442	39	18	accuracy	accuracy	NOUN
ijassa-1442	39	19	,	,	PUNCT
ijassa-1442	39	20	as	as	ADV
ijassa-1442	39	21	well	well	ADV
ijassa-1442	39	22	as	as	ADP
ijassa-1442	39	23	to	to	PART
ijassa-1442	39	24	compare	compare	VERB
ijassa-1442	39	25	fair	fair	ADJ
ijassa-1442	39	26	metrics	metric	NOUN
ijassa-1442	39	27	and	and	CCONJ
ijassa-1442	39	28	accuracy	accuracy	NOUN
ijassa-1442	39	29	in	in	ADP
ijassa-1442	39	30	different	different	ADJ
ijassa-1442	39	31	approaches	approach	NOUN
ijassa-1442	39	32	of	of	ADP
ijassa-1442	39	33	privacy	privacy	NOUN
ijassa-1442	39	34	protection	protection	NOUN
ijassa-1442	39	35	in	in	ADP
ijassa-1442	39	36	different	different	ADJ
ijassa-1442	39	37	machine	machine	NOUN
ijassa-1442	39	38	learning	learning	NOUN
ijassa-1442	39	39	models	model	NOUN
ijassa-1442	39	40	.	.	PUNCT
ijassa-1442	40	1			PRON
ijassa-1442	40	2	what	what	PRON
ijassa-1442	40	3	is	be	AUX
ijassa-1442	40	4	the	the	DET
ijassa-1442	40	5	effect	effect	NOUN
ijassa-1442	40	6	of	of	ADP
ijassa-1442	40	7	privacy	privacy	NOUN
ijassa-1442	40	8	during	during	ADP
ijassa-1442	40	9	encoding	encoding	NOUN
ijassa-1442	40	10	process	process	NOUN
ijassa-1442	40	11	on	on	ADP
ijassa-1442	40	12	fairness	fairness	NOUN
ijassa-1442	40	13	in	in	ADP
ijassa-1442	40	14	machine	machine	NOUN
ijassa-1442	40	15	learning	learning	NOUN
ijassa-1442	40	16	models	model	NOUN
ijassa-1442	40	17	?	?	PUNCT
ijassa-1442	41	1			X
ijassa-1442	41	2	how	how	SCONJ
ijassa-1442	41	3	does	do	VERB
ijassa-1442	41	4	privacy	privacy	NOUN
ijassa-1442	41	5	during	during	ADP
ijassa-1442	41	6	encoding	encoding	NOUN
ijassa-1442	41	7	process	process	NOUN
ijassa-1442	41	8	impact	impact	VERB
ijassa-1442	41	9	the	the	DET
ijassa-1442	41	10	accuracy	accuracy	NOUN
ijassa-1442	41	11	of	of	ADP
ijassa-1442	41	12	machine	machine	NOUN
ijassa-1442	41	13	learning	learning	NOUN
ijassa-1442	41	14	models	model	NOUN
ijassa-1442	41	15	?	?	PUNCT
ijassa-1442	42	1			X
ijassa-1442	42	2	how	how	SCONJ
ijassa-1442	42	3	do	do	VERB
ijassa-1442	42	4	different	different	ADJ
ijassa-1442	42	5	privacy	privacy	NOUN
ijassa-1442	42	6	strategies	strategy	NOUN
ijassa-1442	42	7	impact	impact	NOUN
ijassa-1442	42	8	fairness	fairness	NOUN
ijassa-1442	42	9	metrics	metric	NOUN
ijassa-1442	42	10	in	in	ADP
ijassa-1442	42	11	machine	machine	NOUN
ijassa-1442	42	12	learning	learning	NOUN
ijassa-1442	42	13	models	model	NOUN
ijassa-1442	42	14	?	?	PUNCT
ijassa-1442	42	15			X
ijassa-1442	43	1	how	how	SCONJ
ijassa-1442	43	2	do	do	AUX
ijassa-1442	43	3	the	the	DET
ijassa-1442	43	4	different	different	ADJ
ijassa-1442	43	5	privacy	privacy	NOUN
ijassa-1442	43	6	strategies	strategy	NOUN
ijassa-1442	43	7	impact	impact	NOUN
ijassa-1442	43	8	on	on	ADP
ijassa-1442	43	9	accuracy	accuracy	NOUN
ijassa-1442	43	10	in	in	ADP
ijassa-1442	43	11	machine	machine	NOUN
ijassa-1442	43	12	learning	learning	NOUN
ijassa-1442	43	13	models	model	NOUN
ijassa-1442	43	14	?	?	PUNCT
ijassa-1442	44	1			X
ijassa-1442	44	2	how	how	SCONJ
ijassa-1442	44	3	do	do	AUX
ijassa-1442	44	4	the	the	DET
ijassa-1442	44	5	different	different	ADJ
ijassa-1442	44	6	approaches	approach	NOUN
ijassa-1442	44	7	in	in	ADP
ijassa-1442	44	8	models	model	NOUN
ijassa-1442	44	9	impact	impact	NOUN
ijassa-1442	44	10	on	on	ADP
ijassa-1442	44	11	ability	ability	NOUN
ijassa-1442	44	12	to	to	PART
ijassa-1442	44	13	balance	balance	VERB
ijassa-1442	44	14	fairness	fairness	NOUN
ijassa-1442	44	15	and	and	CCONJ
ijassa-1442	44	16	accuracy	accuracy	NOUN
ijassa-1442	44	17	while	while	SCONJ
ijassa-1442	44	18	privacy	privacy	NOUN
ijassa-1442	44	19	in	in	ADP
ijassa-1442	44	20	machine	machine	NOUN
ijassa-1442	44	21	learning	learning	NOUN
ijassa-1442	44	22	models	model	NOUN
ijassa-1442	44	23	?	?	PUNCT
ijassa-1442	45	1			X
ijassa-1442	45	2	how	how	SCONJ
ijassa-1442	45	3	do	do	VERB
ijassa-1442	45	4	different	different	ADJ
ijassa-1442	45	5	datasets	dataset	NOUN
ijassa-1442	45	6	configurations	configuration	NOUN
ijassa-1442	45	7	impact	impact	NOUN
ijassa-1442	45	8	on	on	ADP
ijassa-1442	45	9	fairness	fairness	NOUN
ijassa-1442	45	10	and	and	CCONJ
ijassa-1442	45	11	accuracy	accuracy	NOUN
ijassa-1442	45	12	results	result	NOUN
ijassa-1442	45	13	?	?	PUNCT
ijassa-1442	46	1	2	2	X
ijassa-1442	46	2	.	.	X
ijassa-1442	46	3	background	background	NOUN
ijassa-1442	46	4	in	in	ADP
ijassa-1442	46	5	this	this	DET
ijassa-1442	46	6	section	section	NOUN
ijassa-1442	46	7	,	,	PUNCT
ijassa-1442	46	8	we	we	PRON
ijassa-1442	46	9	discuss	discuss	VERB
ijassa-1442	46	10	the	the	DET
ijassa-1442	46	11	fundamental	fundamental	ADJ
ijassa-1442	46	12	privacy	privacy	NOUN
ijassa-1442	46	13	and	and	CCONJ
ijassa-1442	46	14	fairness	fairness	NOUN
ijassa-1442	46	15	concepts	concept	NOUN
ijassa-1442	46	16	used	use	VERB
ijassa-1442	46	17	throughout	throughout	ADP
ijassa-1442	46	18	the	the	DET
ijassa-1442	46	19	work	work	NOUN
ijassa-1442	46	20	.	.	PUNCT
ijassa-1442	47	1	2.1	2.1	NUM
ijassa-1442	47	2	.	.	PUNCT
ijassa-1442	47	3	differential	differential	PROPN
ijassa-1442	47	4	privacy	privacy	PROPN
ijassa-1442	47	5	differential	differential	PROPN
ijassa-1442	47	6	privacy	privacy	NOUN
ijassa-1442	47	7	is	be	AUX
ijassa-1442	47	8	a	a	DET
ijassa-1442	47	9	set	set	NOUN
ijassa-1442	47	10	of	of	ADP
ijassa-1442	47	11	methods	method	NOUN
ijassa-1442	47	12	that	that	PRON
ijassa-1442	47	13	provide	provide	VERB
ijassa-1442	47	14	the	the	DET
ijassa-1442	47	15	most	most	ADV
ijassa-1442	47	16	accurate	accurate	ADJ
ijassa-1442	47	17	queries	query	NOUN
ijassa-1442	47	18	to	to	ADP
ijassa-1442	47	19	a	a	DET
ijassa-1442	47	20	statistical	statistical	ADJ
ijassa-1442	47	21	database	database	NOUN
ijassa-1442	47	22	while	while	SCONJ
ijassa-1442	47	23	minimizing	minimize	VERB
ijassa-1442	47	24	the	the	DET
ijassa-1442	47	25	possibility	possibility	NOUN
ijassa-1442	47	26	of	of	ADP
ijassa-1442	47	27	identifying	identify	VERB
ijassa-1442	47	28	individual	individual	ADJ
ijassa-1442	47	29	records	record	NOUN
ijassa-1442	47	30	in	in	ADP
ijassa-1442	47	31	it	it	PRON
ijassa-1442	47	32	.	.	PUNCT
ijassa-1442	48	1	let	let	AUX
ijassa-1442	48	2	be	be	AUX
ijassa-1442	48	3	a	a	DET
ijassa-1442	48	4	positive	positive	ADJ
ijassa-1442	48	5	real	real	ADJ
ijassa-1442	48	6	number	number	NOUN
ijassa-1442	48	7	and	and	CCONJ
ijassa-1442	48	8	be	be	AUX
ijassa-1442	48	9	a	a	DET
ijassa-1442	48	10	probabilistic	probabilistic	ADJ
ijassa-1442	48	11	algorithm	algorithm	NOUN
ijassa-1442	48	12	that	that	PRON
ijassa-1442	48	13	takes	take	VERB
ijassa-1442	48	14	a	a	DET
ijassa-1442	48	15	set	set	NOUN
ijassa-1442	48	16	of	of	ADP
ijassa-1442	48	17	data	datum	NOUN
ijassa-1442	48	18	as	as	ADP
ijassa-1442	48	19	input	input	NOUN
ijassa-1442	48	20	(	(	PUNCT
ijassa-1442	48	21	represents	represent	VERB
ijassa-1442	48	22	the	the	DET
ijassa-1442	48	23	actions	action	NOUN
ijassa-1442	48	24	of	of	ADP
ijassa-1442	48	25	a	a	DET
ijassa-1442	48	26	trusted	trust	VERB
ijassa-1442	48	27	party	party	NOUN
ijassa-1442	48	28	that	that	PRON
ijassa-1442	48	29	has	have	VERB
ijassa-1442	48	30	the	the	DET
ijassa-1442	48	31	data	datum	NOUN
ijassa-1442	48	32	)	)	PUNCT
ijassa-1442	48	33	.	.	PUNCT
ijassa-1442	49	1	algorithm	algorithm	PROPN
ijassa-1442	49	2	is	be	AUX
ijassa-1442	49	3	differentially	differentially	ADV
ijassa-1442	49	4	private	private	ADJ
ijassa-1442	49	5	if	if	SCONJ
ijassa-1442	49	6	for	for	ADP
ijassa-1442	49	7	all	all	DET
ijassa-1442	49	8	datasets	dataset	NOUN
ijassa-1442	49	9	and	and	CCONJ
ijassa-1442	49	10	the	the	DET
ijassa-1442	49	11	following	follow	VERB
ijassa-1442	49	12	expression	expression	NOUN
ijassa-1442	49	13	is	be	AUX
ijassa-1442	49	14	executed	execute	VERB
ijassa-1442	49	15	[	[	PUNCT
ijassa-1442	49	16	11	11	NUM
ijassa-1442	49	17	]	]	PUNCT
ijassa-1442	49	18	.	.	PUNCT
ijassa-1442	50	1	where	where	SCONJ
ijassa-1442	50	2	and	and	CCONJ
ijassa-1442	50	3	are	be	AUX
ijassa-1442	50	4	differing	differ	VERB
ijassa-1442	50	5	datasets	dataset	NOUN
ijassa-1442	50	6	by	by	ADP
ijassa-1442	50	7	at	at	ADP
ijassa-1442	50	8	most	most	ADV
ijassa-1442	50	9	one	one	NUM
ijassa-1442	50	10	element	element	NOUN
ijassa-1442	50	11	,	,	PUNCT
ijassa-1442	50	12	and	and	CCONJ
ijassa-1442	50	13	denotes	denote	VERB
ijassa-1442	50	14	the	the	DET
ijassa-1442	50	15	probability	probability	NOUN
ijassa-1442	50	16	that	that	PRON
ijassa-1442	50	17	is	be	AUX
ijassa-1442	50	18	the	the	DET
ijassa-1442	50	19	output	output	NOUN
ijassa-1442	50	20	of	of	ADP
ijassa-1442	50	21	.	.	PUNCT
ijassa-1442	51	1	according	accord	VERB
ijassa-1442	51	2	to	to	ADP
ijassa-1442	51	3	this	this	DET
ijassa-1442	51	4	definition	definition	NOUN
ijassa-1442	51	5	,	,	PUNCT
ijassa-1442	51	6	differential	differential	ADJ
ijassa-1442	51	7	privacy	privacy	NOUN
ijassa-1442	51	8	is	be	AUX
ijassa-1442	51	9	a	a	DET
ijassa-1442	51	10	condition	condition	NOUN
ijassa-1442	51	11	of	of	ADP
ijassa-1442	51	12	the	the	DET
ijassa-1442	51	13	data	data	NOUN
ijassa-1442	51	14	publishing	publishing	NOUN
ijassa-1442	51	15	mechanism	mechanism	NOUN
ijassa-1442	51	16	(	(	PUNCT
ijassa-1442	51	17	that	that	PRON
ijassa-1442	51	18	is	is	ADV
ijassa-1442	51	19	,	,	PUNCT
ijassa-1442	51	20	determined	determine	VERB
ijassa-1442	51	21	by	by	ADP
ijassa-1442	51	22	the	the	DET
ijassa-1442	51	23	trusted	trust	VERB
ijassa-1442	51	24	party	party	NOUN
ijassa-1442	51	25	that	that	PRON
ijassa-1442	51	26	releases	release	VERB
ijassa-1442	51	27	information	information	NOUN
ijassa-1442	51	28	about	about	ADP
ijassa-1442	51	29	the	the	DET
ijassa-1442	51	30	data	datum	NOUN
ijassa-1442	51	31	set	set	NOUN
ijassa-1442	51	32	)	)	PUNCT
ijassa-1442	51	33	,	,	PUNCT
ijassa-1442	51	34	not	not	PART
ijassa-1442	51	35	the	the	DET
ijassa-1442	51	36	data	datum	NOUN
ijassa-1442	51	37	set	set	VERB
ijassa-1442	51	38	itself	itself	PRON
ijassa-1442	51	39	.	.	PUNCT
ijassa-1442	52	1	intuitively	intuitively	ADV
ijassa-1442	52	2	,	,	PUNCT
ijassa-1442	52	3	this	this	PRON
ijassa-1442	52	4	means	mean	VERB
ijassa-1442	52	5	that	that	SCONJ
ijassa-1442	52	6	for	for	ADP
ijassa-1442	52	7	any	any	DET
ijassa-1442	52	8	two	two	NUM
ijassa-1442	52	9	similar	similar	ADJ
ijassa-1442	52	10	datasets	dataset	NOUN
ijassa-1442	52	11	,	,	PUNCT
ijassa-1442	52	12	the	the	DET
ijassa-1442	52	13	differential	differential	ADJ
ijassa-1442	52	14	private	private	ADJ
ijassa-1442	52	15	algorithm	algorithm	NOUN
ijassa-1442	52	16	will	will	AUX
ijassa-1442	52	17	behave	behave	VERB
ijassa-1442	52	18	approximately	approximately	ADV
ijassa-1442	52	19	the	the	DET
ijassa-1442	52	20	same	same	ADJ
ijassa-1442	52	21	on	on	ADP
ijassa-1442	52	22	both	both	DET
ijassa-1442	52	23	datasets	dataset	NOUN
ijassa-1442	52	24	.	.	PUNCT
ijassa-1442	53	1	2.2	2.2	NUM
ijassa-1442	53	2	.	.	PUNCT
ijassa-1442	53	3	privacy	privacy	NOUN
ijassa-1442	53	4	preservation	preservation	NOUN
ijassa-1442	53	5	(	(	PUNCT
ijassa-1442	53	6	dp	dp	NOUN
ijassa-1442	53	7	-	-	PUNCT
ijassa-1442	53	8	sgd	sgd	NOUN
ijassa-1442	53	9	)	)	PUNCT
ijassa-1442	53	10	stochastic	stochastic	ADJ
ijassa-1442	53	11	gradient	gradient	ADJ
ijassa-1442	53	12	descent	descent	NOUN
ijassa-1442	53	13	(	(	PUNCT
ijassa-1442	53	14	sgd	sgd	PROPN
ijassa-1442	53	15	)	)	PUNCT
ijassa-1442	53	16	is	be	AUX
ijassa-1442	53	17	an	an	DET
ijassa-1442	53	18	iterative	iterative	NOUN
ijassa-1442	53	19	method	method	NOUN
ijassa-1442	53	20	for	for	ADP
ijassa-1442	53	21	optimizing	optimize	VERB
ijassa-1442	53	22	differentiable	differentiable	ADJ
ijassa-1442	53	23	objective	objective	ADJ
ijassa-1442	53	24	functions	function	NOUN
ijassa-1442	53	25	.	.	PUNCT
ijassa-1442	54	1	it	it	PRON
ijassa-1442	54	2	updates	update	VERB
ijassa-1442	54	3	the	the	DET
ijassa-1442	54	4	weights	weight	NOUN
ijassa-1442	54	5	and	and	CCONJ
ijassa-1442	54	6	biases	bias	NOUN
ijassa-1442	54	7	by	by	ADP
ijassa-1442	54	8	calculating	calculate	VERB
ijassa-1442	54	9	the	the	DET
ijassa-1442	54	10	gradient	gradient	NOUN
ijassa-1442	54	11	of	of	ADP
ijassa-1442	54	12	the	the	DET
ijassa-1442	54	13	loss	loss	NOUN
ijassa-1442	54	14	function	function	NOUN
ijassa-1442	54	15	for	for	ADP
ijassa-1442	54	16	small	small	ADJ
ijassa-1442	54	17	data	datum	NOUN
ijassa-1442	54	18	packets	packet	NOUN
ijassa-1442	54	19	[	[	X
ijassa-1442	54	20	3	3	NUM
ijassa-1442	54	21	]	]	PUNCT
ijassa-1442	54	22	.	.	PUNCT
ijassa-1442	55	1	dp	dp	ADJ
ijassa-1442	55	2	-	-	ADJ
ijassa-1442	55	3	sgd	sgd	NOUN
ijassa-1442	55	4	[	[	X
ijassa-1442	55	5	26	26	NUM
ijassa-1442	55	6	]	]	PUNCT
ijassa-1442	55	7	is	be	AUX
ijassa-1442	55	8	a	a	DET
ijassa-1442	55	9	modification	modification	NOUN
ijassa-1442	55	10	of	of	ADP
ijassa-1442	55	11	the	the	DET
ijassa-1442	55	12	stochastic	stochastic	ADJ
ijassa-1442	55	13	gradient	gradient	NOUN
ijassa-1442	55	14	42	42	NUM
ijassa-1442	55	15	a.	a.	NOUN
ijassa-1442	55	16	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	55	17	,	,	PUNCT
ijassa-1442	55	18	r.	r.	PROPN
ijassa-1442	55	19	sabitov	sabitov	PROPN
ijassa-1442	55	20	,	,	PUNCT
ijassa-1442	55	21	g.	g.	PROPN
ijassa-1442	55	22	smirnova	smirnova	PROPN
ijassa-1442	55	23	,	,	PUNCT
ijassa-1442	56	1	sh	sh	PROPN
ijassa-1442	56	2	.	.	PUNCT
ijassa-1442	56	3	sabitov	sabitov	PROPN
ijassa-1442	56	4	copyright	copyright	NOUN
ijassa-1442	56	5	©	©	PROPN
ijassa-1442	56	6	2023	2023	NUM
ijassa-1442	56	7	assa	assa	PROPN
ijassa-1442	56	8	adv	adv	PROPN
ijassa-1442	56	9	.	.	PUNCT
ijassa-1442	57	1	in	in	ADP
ijassa-1442	57	2	systems	system	NOUN
ijassa-1442	57	3	science	science	NOUN
ijassa-1442	57	4	and	and	CCONJ
ijassa-1442	57	5	appl	appl	NOUN
ijassa-1442	57	6	.	.	PUNCT
ijassa-1442	58	1	(	(	PUNCT
ijassa-1442	58	2	2023	2023	NUM
ijassa-1442	58	3	)	)	PUNCT
ijassa-1442	58	4	descent	descent	NOUN
ijassa-1442	58	5	algorithm	algorithm	NOUN
ijassa-1442	58	6	that	that	PRON
ijassa-1442	58	7	provides	provide	VERB
ijassa-1442	58	8	provable	provable	ADJ
ijassa-1442	58	9	privacy	privacy	NOUN
ijassa-1442	58	10	guarantees	guarantee	NOUN
ijassa-1442	58	11	.	.	PUNCT
ijassa-1442	59	1	it	it	PRON
ijassa-1442	59	2	differs	differ	VERB
ijassa-1442	59	3	from	from	ADP
ijassa-1442	59	4	sgd	sgd	PROPN
ijassa-1442	59	5	in	in	SCONJ
ijassa-1442	59	6	that	that	SCONJ
ijassa-1442	59	7	it	it	PRON
ijassa-1442	59	8	limits	limit	VERB
ijassa-1442	59	9	the	the	DET
ijassa-1442	59	10	sensitivity	sensitivity	NOUN
ijassa-1442	59	11	of	of	ADP
ijassa-1442	59	12	each	each	DET
ijassa-1442	59	13	gradient	gradient	NOUN
ijassa-1442	59	14	and	and	CCONJ
ijassa-1442	59	15	works	work	VERB
ijassa-1442	59	16	in	in	ADP
ijassa-1442	59	17	tandem	tandem	NOUN
ijassa-1442	59	18	with	with	ADP
ijassa-1442	59	19	the	the	DET
ijassa-1442	59	20	moments	moment	NOUN
ijassa-1442	59	21	accountant	accountant	NOUN
ijassa-1442	59	22	algorithm	algorithm	NOUN
ijassa-1442	59	23	to	to	PART
ijassa-1442	59	24	amplify	amplify	VERB
ijassa-1442	59	25	and	and	CCONJ
ijassa-1442	59	26	track	track	VERB
ijassa-1442	59	27	the	the	DET
ijassa-1442	59	28	loss	loss	NOUN
ijassa-1442	59	29	of	of	ADP
ijassa-1442	59	30	privacy	privacy	NOUN
ijassa-1442	59	31	when	when	SCONJ
ijassa-1442	59	32	the	the	DET
ijassa-1442	59	33	weight	weight	NOUN
ijassa-1442	59	34	is	be	AUX
ijassa-1442	59	35	updated	update	VERB
ijassa-1442	59	36	.	.	PUNCT
ijassa-1442	60	1	the	the	DET
ijassa-1442	60	2	moments	moment	NOUN
ijassa-1442	60	3	accountant	accountant	NOUN
ijassa-1442	60	4	accumulates	accumulate	VERB
ijassa-1442	60	5	and	and	CCONJ
ijassa-1442	60	6	tracks	track	VERB
ijassa-1442	60	7	privacy	privacy	NOUN
ijassa-1442	60	8	spending	spending	NOUN
ijassa-1442	60	9	while	while	SCONJ
ijassa-1442	60	10	training	train	VERB
ijassa-1442	60	11	deep	deep	ADJ
ijassa-1442	60	12	neural	neural	ADJ
ijassa-1442	60	13	networks	network	NOUN
ijassa-1442	60	14	.	.	PUNCT
ijassa-1442	61	1	moments	moment	NOUN
ijassa-1442	61	2	accountant	accountant	NOUN
ijassa-1442	61	3	greatly	greatly	ADV
ijassa-1442	61	4	improves	improve	VERB
ijassa-1442	61	5	on	on	ADP
ijassa-1442	61	6	earlier	early	ADJ
ijassa-1442	61	7	sgd	sgd	PROPN
ijassa-1442	61	8	privacy	privacy	NOUN
ijassa-1442	61	9	analysis	analysis	NOUN
ijassa-1442	61	10	and	and	CCONJ
ijassa-1442	61	11	provides	provide	VERB
ijassa-1442	61	12	meaningful	meaningful	ADJ
ijassa-1442	61	13	privacy	privacy	NOUN
ijassa-1442	61	14	guarantees	guarantee	NOUN
ijassa-1442	61	15	for	for	ADP
ijassa-1442	61	16	deep	deep	ADJ
ijassa-1442	61	17	learning	learning	NOUN
ijassa-1442	61	18	trained	train	VERB
ijassa-1442	61	19	on	on	ADP
ijassa-1442	61	20	real	real	ADJ
ijassa-1442	61	21	-	-	PUNCT
ijassa-1442	61	22	size	size	NOUN
ijassa-1442	61	23	datasets	dataset	NOUN
ijassa-1442	61	24	.	.	PUNCT
ijassa-1442	62	1	to	to	PART
ijassa-1442	62	2	ensure	ensure	VERB
ijassa-1442	62	3	that	that	SCONJ
ijassa-1442	62	4	the	the	DET
ijassa-1442	62	5	sgd	sgd	NOUN
ijassa-1442	62	6	is	be	AUX
ijassa-1442	62	7	differentially	differentially	ADV
ijassa-1442	62	8	private	private	ADJ
ijassa-1442	62	9	(	(	PUNCT
ijassa-1442	62	10	i.e.	i.e.	X
ijassa-1442	62	11	dp	dp	NOUN
ijassa-1442	62	12	-	-	PUNCT
ijassa-1442	62	13	sgd	sgd	NOUN
ijassa-1442	62	14	)	)	PUNCT
ijassa-1442	62	15	,	,	PUNCT
ijassa-1442	62	16	two	two	NUM
ijassa-1442	62	17	modifications	modification	NOUN
ijassa-1442	62	18	must	must	AUX
ijassa-1442	62	19	be	be	AUX
ijassa-1442	62	20	made	make	VERB
ijassa-1442	62	21	to	to	ADP
ijassa-1442	62	22	the	the	DET
ijassa-1442	62	23	original	original	ADJ
ijassa-1442	62	24	sgd	sgd	NOUN
ijassa-1442	62	25	algorithm	algorithm	NOUN
ijassa-1442	62	26	.	.	PUNCT
ijassa-1442	63	1	first	first	ADV
ijassa-1442	63	2	,	,	PUNCT
ijassa-1442	63	3	the	the	DET
ijassa-1442	63	4	sensitivity	sensitivity	NOUN
ijassa-1442	63	5	of	of	ADP
ijassa-1442	63	6	each	each	DET
ijassa-1442	63	7	gradient	gradient	NOUN
ijassa-1442	63	8	must	must	AUX
ijassa-1442	63	9	be	be	AUX
ijassa-1442	63	10	limited	limit	VERB
ijassa-1442	63	11	.	.	PUNCT
ijassa-1442	64	1	this	this	PRON
ijassa-1442	64	2	is	be	AUX
ijassa-1442	64	3	done	do	VERB
ijassa-1442	64	4	by	by	ADP
ijassa-1442	64	5	trimming	trim	VERB
ijassa-1442	64	6	the	the	DET
ijassa-1442	64	7	gradient	gradient	NOUN
ijassa-1442	64	8	in	in	ADP
ijassa-1442	64	9	normal	normal	ADJ
ijassa-1442	64	10	.	.	PUNCT
ijassa-1442	65	1	second	second	ADJ
ijassa-1442	65	2	,	,	PUNCT
ijassa-1442	65	3	random	random	ADJ
ijassa-1442	65	4	noise	noise	NOUN
ijassa-1442	65	5	is	be	AUX
ijassa-1442	65	6	applied	apply	VERB
ijassa-1442	65	7	to	to	ADP
ijassa-1442	65	8	the	the	DET
ijassa-1442	65	9	previously	previously	ADV
ijassa-1442	65	10	clipped	clip	VERB
ijassa-1442	65	11	gradient	gradient	NOUN
ijassa-1442	65	12	by	by	ADP
ijassa-1442	65	13	multiplying	multiply	VERB
ijassa-1442	65	14	its	its	PRON
ijassa-1442	65	15	sum	sum	NOUN
ijassa-1442	65	16	by	by	ADP
ijassa-1442	65	17	the	the	DET
ijassa-1442	65	18	learning	learning	NOUN
ijassa-1442	65	19	rate	rate	NOUN
ijassa-1442	65	20	and	and	CCONJ
ijassa-1442	65	21	then	then	ADV
ijassa-1442	65	22	using	use	VERB
ijassa-1442	65	23	it	it	PRON
ijassa-1442	65	24	to	to	PART
ijassa-1442	65	25	update	update	VERB
ijassa-1442	65	26	the	the	DET
ijassa-1442	65	27	model	model	NOUN
ijassa-1442	65	28	parameters	parameter	NOUN
ijassa-1442	65	29	.	.	PUNCT
ijassa-1442	66	1	2.3	2.3	NUM
ijassa-1442	66	2	.	.	PUNCT
ijassa-1442	67	1	fairness	fairness	NOUN
ijassa-1442	67	2	fair	fair	ADJ
ijassa-1442	67	3	modeling	modeling	NOUN
ijassa-1442	67	4	is	be	AUX
ijassa-1442	67	5	an	an	DET
ijassa-1442	67	6	area	area	NOUN
ijassa-1442	67	7	of	of	ADP
ijassa-1442	67	8	artificial	artificial	ADJ
ijassa-1442	67	9	intelligence	intelligence	NOUN
ijassa-1442	67	10	that	that	PRON
ijassa-1442	67	11	ensures	ensure	VERB
ijassa-1442	67	12	that	that	SCONJ
ijassa-1442	67	13	machine	machine	NOUN
ijassa-1442	67	14	simulation	simulation	NOUN
ijassa-1442	67	15	results	result	NOUN
ijassa-1442	67	16	are	be	AUX
ijassa-1442	67	17	not	not	PART
ijassa-1442	67	18	affected	affect	VERB
ijassa-1442	67	19	by	by	ADP
ijassa-1442	67	20	protected	protect	VERB
ijassa-1442	67	21	attributes	attribute	NOUN
ijassa-1442	67	22	such	such	ADJ
ijassa-1442	67	23	as	as	ADP
ijassa-1442	67	24	gender	gender	NOUN
ijassa-1442	67	25	,	,	PUNCT
ijassa-1442	67	26	race	race	NOUN
ijassa-1442	67	27	,	,	PUNCT
ijassa-1442	67	28	religion	religion	NOUN
ijassa-1442	67	29	,	,	PUNCT
ijassa-1442	67	30	sexual	sexual	ADJ
ijassa-1442	67	31	orientation	orientation	NOUN
ijassa-1442	67	32	,	,	PUNCT
ijassa-1442	67	33	etc	etc	X
ijassa-1442	67	34	.	.	X
ijassa-1442	68	1	in	in	ADP
ijassa-1442	68	2	this	this	DET
ijassa-1442	68	3	work	work	NOUN
ijassa-1442	68	4	we	we	PRON
ijassa-1442	68	5	will	will	AUX
ijassa-1442	68	6	use	use	VERB
ijassa-1442	68	7	specific	specific	ADJ
ijassa-1442	68	8	metrics	metric	NOUN
ijassa-1442	68	9	that	that	PRON
ijassa-1442	68	10	can	can	AUX
ijassa-1442	68	11	be	be	AUX
ijassa-1442	68	12	used	use	VERB
ijassa-1442	68	13	to	to	PART
ijassa-1442	68	14	evaluate	evaluate	VERB
ijassa-1442	68	15	the	the	DET
ijassa-1442	68	16	fairness	fairness	NOUN
ijassa-1442	68	17	of	of	ADP
ijassa-1442	68	18	a	a	DET
ijassa-1442	68	19	model	model	NOUN
ijassa-1442	68	20	.	.	PUNCT
ijassa-1442	69	1	the	the	DET
ijassa-1442	69	2	most	most	ADV
ijassa-1442	69	3	commonly	commonly	ADV
ijassa-1442	69	4	used	use	VERB
ijassa-1442	69	5	measures	measure	NOUN
ijassa-1442	69	6	of	of	ADP
ijassa-1442	69	7	fairness	fairness	NOUN
ijassa-1442	69	8	are	be	AUX
ijassa-1442	69	9	statistical	statistical	ADJ
ijassa-1442	69	10	(	(	PUNCT
ijassa-1442	69	11	demographic	demographic	ADJ
ijassa-1442	69	12	)	)	PUNCT
ijassa-1442	69	13	parity	parity	NOUN
ijassa-1442	69	14	and	and	CCONJ
ijassa-1442	69	15	equalized	equalize	VERB
ijassa-1442	69	16	odds	odd	NOUN
ijassa-1442	69	17	[	[	X
ijassa-1442	69	18	19	19	NUM
ijassa-1442	69	19	,	,	PUNCT
ijassa-1442	69	20	27	27	NUM
ijassa-1442	69	21	]	]	PUNCT
ijassa-1442	69	22	.	.	PUNCT
ijassa-1442	70	1	the	the	DET
ijassa-1442	70	2	definition	definition	NOUN
ijassa-1442	70	3	of	of	ADP
ijassa-1442	70	4	these	these	DET
ijassa-1442	70	5	metrics	metric	NOUN
ijassa-1442	70	6	is	be	AUX
ijassa-1442	70	7	given	give	VERB
ijassa-1442	70	8	below	below	ADV
ijassa-1442	70	9	.	.	PUNCT
ijassa-1442	71	1	given	give	VERB
ijassa-1442	71	2	a	a	DET
ijassa-1442	71	3	dataset	dataset	NOUN
ijassa-1442	71	4	,	,	PUNCT
ijassa-1442	71	5	where	where	SCONJ
ijassa-1442	71	6	is	be	AUX
ijassa-1442	71	7	the	the	DET
ijassa-1442	71	8	feature	feature	NOUN
ijassa-1442	71	9	vector	vector	NOUN
ijassa-1442	71	10	,	,	PUNCT
ijassa-1442	71	11	the	the	DET
ijassa-1442	71	12	label	label	NOUN
ijassa-1442	71	13	,	,	PUNCT
ijassa-1442	71	14	and	and	CCONJ
ijassa-1442	71	15	the	the	DET
ijassa-1442	71	16	binary	binary	PROPN
ijassa-1442	71	17	protected	protect	VERB
ijassa-1442	71	18	attribute	attribute	NOUN
ijassa-1442	71	19	(	(	PUNCT
ijassa-1442	71	20	e.g.	e.g.	ADV
ijassa-1442	71	21	gender	gender	NOUN
ijassa-1442	71	22	,	,	PUNCT
ijassa-1442	71	23	race	race	NOUN
ijassa-1442	71	24	,	,	PUNCT
ijassa-1442	71	25	etc	etc	X
ijassa-1442	71	26	.	.	X
ijassa-1442	71	27	)	)	PUNCT
ijassa-1442	71	28	.	.	PUNCT
ijassa-1442	72	1	the	the	DET
ijassa-1442	72	2	goal	goal	NOUN
ijassa-1442	72	3	is	be	AUX
ijassa-1442	72	4	to	to	PART
ijassa-1442	72	5	learn	learn	VERB
ijassa-1442	72	6	a	a	DET
ijassa-1442	72	7	new	new	ADJ
ijassa-1442	72	8	representation	representation	NOUN
ijassa-1442	72	9	,	,	PUNCT
ijassa-1442	72	10	such	such	ADJ
ijassa-1442	72	11	that	that	PRON
ijassa-1442	72	12	will	will	AUX
ijassa-1442	72	13	satisfy	satisfy	VERB
ijassa-1442	72	14	a	a	DET
ijassa-1442	72	15	certain	certain	ADJ
ijassa-1442	72	16	fairness	fairness	NOUN
ijassa-1442	72	17	criteria	criterion	NOUN
ijassa-1442	72	18	such	such	ADJ
ijassa-1442	72	19	as	as	ADP
ijassa-1442	72	20	:	:	PUNCT
ijassa-1442	72	21			NOUN
ijassa-1442	72	22	statistical	statistical	ADJ
ijassa-1442	72	23	parity	parity	NOUN
ijassa-1442	72	24	:	:	PUNCT
ijassa-1442	72	25	a	a	DET
ijassa-1442	72	26	predictor	predictor	NOUN
ijassa-1442	72	27	trained	train	VERB
ijassa-1442	72	28	on	on	ADP
ijassa-1442	72	29	must	must	AUX
ijassa-1442	72	30	satisfy	satisfy	VERB
ijassa-1442	72	31	:	:	PUNCT
ijassa-1442	72	32			PRON
ijassa-1442	72	33	equalized	equalize	VERB
ijassa-1442	72	34	odds	odd	NOUN
ijassa-1442	72	35	:	:	PUNCT
ijassa-1442	72	36	a	a	DET
ijassa-1442	72	37	predictor	predictor	NOUN
ijassa-1442	72	38	trained	train	VERB
ijassa-1442	72	39	on	on	ADP
ijassa-1442	72	40	must	must	AUX
ijassa-1442	72	41	satisfy	satisfy	VERB
ijassa-1442	72	42	:	:	PUNCT
ijassa-1442	72	43	3	3	X
ijassa-1442	72	44	.	.	X
ijassa-1442	72	45	related	relate	VERB
ijassa-1442	72	46	work	work	NOUN
ijassa-1442	72	47	the	the	DET
ijassa-1442	72	48	growing	grow	VERB
ijassa-1442	72	49	field	field	NOUN
ijassa-1442	72	50	of	of	ADP
ijassa-1442	72	51	algorithmic	algorithmic	ADJ
ijassa-1442	72	52	fairness	fairness	NOUN
ijassa-1442	72	53	and	and	CCONJ
ijassa-1442	72	54	differential	differential	NOUN
ijassa-1442	72	55	privacy	privacy	NOUN
ijassa-1442	72	56	has	have	AUX
ijassa-1442	72	57	led	lead	VERB
ijassa-1442	72	58	to	to	ADP
ijassa-1442	72	59	the	the	DET
ijassa-1442	72	60	development	development	NOUN
ijassa-1442	72	61	of	of	ADP
ijassa-1442	72	62	numerous	numerous	ADJ
ijassa-1442	72	63	methods	method	NOUN
ijassa-1442	72	64	for	for	ADP
ijassa-1442	72	65	mitigating	mitigate	VERB
ijassa-1442	72	66	bias	bias	NOUN
ijassa-1442	72	67	and	and	CCONJ
ijassa-1442	72	68	ensuring	ensure	VERB
ijassa-1442	72	69	data	datum	NOUN
ijassa-1442	72	70	privacy	privacy	NOUN
ijassa-1442	72	71	.	.	PUNCT
ijassa-1442	73	1	in	in	ADP
ijassa-1442	73	2	recent	recent	ADJ
ijassa-1442	73	3	research	research	NOUN
ijassa-1442	73	4	,	,	PUNCT
ijassa-1442	73	5	the	the	DET
ijassa-1442	73	6	authors	author	NOUN
ijassa-1442	73	7	in	in	ADP
ijassa-1442	73	8	[	[	X
ijassa-1442	73	9	21	21	NUM
ijassa-1442	73	10	]	]	PUNCT
ijassa-1442	73	11	introduce	introduce	VERB
ijassa-1442	73	12	a	a	DET
ijassa-1442	73	13	framework	framework	NOUN
ijassa-1442	73	14	for	for	ADP
ijassa-1442	73	15	evaluating	evaluate	VERB
ijassa-1442	73	16	and	and	CCONJ
ijassa-1442	73	17	analyzing	analyze	VERB
ijassa-1442	73	18	bias	bias	NOUN
ijassa-1442	73	19	mitigation	mitigation	NOUN
ijassa-1442	73	20	techniques	technique	NOUN
ijassa-1442	73	21	by	by	ADP
ijassa-1442	73	22	using	use	VERB
ijassa-1442	73	23	a	a	DET
ijassa-1442	73	24	synthetic	synthetic	ADJ
ijassa-1442	73	25	dataset	dataset	NOUN
ijassa-1442	73	26	and	and	CCONJ
ijassa-1442	73	27	controlling	control	VERB
ijassa-1442	73	28	different	different	ADJ
ijassa-1442	73	29	components	component	NOUN
ijassa-1442	73	30	of	of	ADP
ijassa-1442	73	31	the	the	DET
ijassa-1442	73	32	data	data	NOUN
ijassa-1442	73	33	generation	generation	NOUN
ijassa-1442	73	34	process	process	NOUN
ijassa-1442	73	35	.	.	PUNCT
ijassa-1442	74	1	the	the	DET
ijassa-1442	74	2	study	study	NOUN
ijassa-1442	74	3	also	also	ADV
ijassa-1442	74	4	analyzes	analyze	VERB
ijassa-1442	74	5	the	the	DET
ijassa-1442	74	6	performance	performance	NOUN
ijassa-1442	74	7	of	of	ADP
ijassa-1442	74	8	several	several	ADJ
ijassa-1442	74	9	model	model	NOUN
ijassa-1442	74	10	architectures	architecture	NOUN
ijassa-1442	74	11	(	(	PUNCT
ijassa-1442	74	12	such	such	ADJ
ijassa-1442	74	13	as	as	ADP
ijassa-1442	74	14	mlp	mlp	PROPN
ijassa-1442	74	15	[	[	X
ijassa-1442	74	16	22	22	NUM
ijassa-1442	74	17	]	]	PUNCT
ijassa-1442	74	18	,	,	PUNCT
ijassa-1442	74	19	cnn	cnn	PROPN
ijassa-1442	75	1	[	[	X
ijassa-1442	75	2	13	13	NUM
ijassa-1442	75	3	]	]	PUNCT
ijassa-1442	75	4	,	,	PUNCT
ijassa-1442	75	5	laftr	laftr	ADP
ijassa-1442	75	6	[	[	X
ijassa-1442	75	7	17	17	NUM
ijassa-1442	75	8	,	,	PUNCT
ijassa-1442	75	9	9	9	NUM
ijassa-1442	75	10	]	]	PUNCT
ijassa-1442	75	11	,	,	PUNCT
ijassa-1442	75	12	cfair	cfair	NOUN
ijassa-1442	75	13	[	[	X
ijassa-1442	75	14	6	6	NUM
ijassa-1442	75	15	]	]	PUNCT
ijassa-1442	75	16	,	,	PUNCT
ijassa-1442	75	17	ffvae	ffvae	NOUN
ijassa-1442	76	1	[	[	X
ijassa-1442	76	2	15	15	NUM
ijassa-1442	76	3	]	]	PUNCT
ijassa-1442	76	4	)	)	PUNCT
ijassa-1442	76	5	on	on	ADP
ijassa-1442	76	6	the	the	DET
ijassa-1442	76	7	adult	adult	NOUN
ijassa-1442	76	8	,	,	PUNCT
ijassa-1442	76	9	cimnist	cimnist	NOUN
ijassa-1442	76	10	datasets	dataset	NOUN
ijassa-1442	76	11	,	,	PUNCT
ijassa-1442	76	12	to	to	PART
ijassa-1442	76	13	understand	understand	VERB
ijassa-1442	76	14	the	the	DET
ijassa-1442	76	15	sources	source	NOUN
ijassa-1442	76	16	and	and	CCONJ
ijassa-1442	76	17	levels	level	NOUN
ijassa-1442	76	18	of	of	ADP
ijassa-1442	76	19	bias	bias	NOUN
ijassa-1442	76	20	.	.	PUNCT
ijassa-1442	77	1	as	as	ADP
ijassa-1442	77	2	an	an	DET
ijassa-1442	77	3	extension	extension	NOUN
ijassa-1442	77	4	to	to	ADP
ijassa-1442	77	5	this	this	DET
ijassa-1442	77	6	article	article	NOUN
ijassa-1442	77	7	,	,	PUNCT
ijassa-1442	77	8	this	this	DET
ijassa-1442	77	9	work	work	NOUN
ijassa-1442	77	10	is	be	AUX
ijassa-1442	77	11	focused	focus	VERB
ijassa-1442	77	12	on	on	ADP
ijassa-1442	77	13	combining	combine	VERB
ijassa-1442	77	14	the	the	DET
ijassa-1442	77	15	principles	principle	NOUN
ijassa-1442	77	16	of	of	ADP
ijassa-1442	77	17	algorithmic	algorithmic	ADJ
ijassa-1442	77	18	fairness	fairness	NOUN
ijassa-1442	77	19	and	and	CCONJ
ijassa-1442	77	20	differential	differential	NOUN
ijassa-1442	77	21	privacy	privacy	NOUN
ijassa-1442	77	22	in	in	ADP
ijassa-1442	77	23	the	the	DET
ijassa-1442	77	24	training	training	NOUN
ijassa-1442	77	25	of	of	ADP
ijassa-1442	77	26	models	model	NOUN
ijassa-1442	77	27	under	under	ADP
ijassa-1442	77	28	adversary	adversary	NOUN
ijassa-1442	77	29	.	.	PUNCT
ijassa-1442	78	1	in	in	ADP
ijassa-1442	78	2	particular	particular	ADJ
ijassa-1442	78	3	,	,	PUNCT
ijassa-1442	78	4	this	this	DET
ijassa-1442	78	5	article	article	NOUN
ijassa-1442	78	6	considers	consider	VERB
ijassa-1442	78	7	the	the	DET
ijassa-1442	78	8	laftr	laftr	ADJ
ijassa-1442	78	9	model	model	NOUN
ijassa-1442	78	10	,	,	PUNCT
ijassa-1442	78	11	which	which	PRON
ijassa-1442	78	12	aims	aim	VERB
ijassa-1442	78	13	to	to	PART
ijassa-1442	78	14	provide	provide	VERB
ijassa-1442	78	15	a	a	DET
ijassa-1442	78	16	fair	fair	ADJ
ijassa-1442	78	17	data	datum	NOUN
ijassa-1442	78	18	while	while	SCONJ
ijassa-1442	78	19	maintaining	maintain	VERB
ijassa-1442	78	20	good	good	ADJ
ijassa-1442	78	21	predictive	predictive	ADJ
ijassa-1442	78	22	accuracy	accuracy	NOUN
ijassa-1442	78	23	.	.	PUNCT
ijassa-1442	79	1	the	the	DET
ijassa-1442	79	2	methodology	methodology	NOUN
ijassa-1442	79	3	is	be	AUX
ijassa-1442	79	4	based	base	VERB
ijassa-1442	79	5	on	on	ADP
ijassa-1442	79	6	the	the	DET
ijassa-1442	79	7	introduction	introduction	NOUN
ijassa-1442	79	8	of	of	ADP
ijassa-1442	79	9	differential	differential	ADJ
ijassa-1442	79	10	privacy	privacy	NOUN
ijassa-1442	79	11	to	to	ADP
ijassa-1442	79	12	model	model	NOUN
ijassa-1442	79	13	training	training	NOUN
ijassa-1442	79	14	.	.	PUNCT
ijassa-1442	80	1	furthermore	furthermore	ADV
ijassa-1442	80	2	,	,	PUNCT
ijassa-1442	80	3	the	the	DET
ijassa-1442	80	4	examination	examination	NOUN
ijassa-1442	80	5	of	of	ADP
ijassa-1442	80	6	combining	combine	VERB
ijassa-1442	80	7	algorithmic	algorithmic	ADJ
ijassa-1442	80	8	fairness	fairness	NOUN
ijassa-1442	80	9	and	and	CCONJ
ijassa-1442	80	10	differential	differential	NOUN
ijassa-1442	80	11	privacy	privacy	NOUN
ijassa-1442	80	12	in	in	ADP
ijassa-1442	80	13	training	training	NOUN
ijassa-1442	80	14	models	model	NOUN
ijassa-1442	80	15	in	in	ADP
ijassa-1442	80	16	the	the	DET
ijassa-1442	80	17	presence	presence	NOUN
ijassa-1442	80	18	of	of	ADP
ijassa-1442	80	19	an	an	DET
ijassa-1442	80	20	adversary	adversary	NOUN
ijassa-1442	80	21	is	be	AUX
ijassa-1442	80	22	extended	extend	VERB
ijassa-1442	80	23	in	in	ADP
ijassa-1442	80	24	other	other	ADJ
ijassa-1442	80	25	studies	study	NOUN
ijassa-1442	80	26	.	.	PUNCT
ijassa-1442	81	1	in	in	ADP
ijassa-1442	81	2	[	[	X
ijassa-1442	81	3	18	18	NUM
ijassa-1442	81	4	]	]	PUNCT
ijassa-1442	81	5	authors	author	NOUN
ijassa-1442	81	6	aim	aim	VERB
ijassa-1442	81	7	to	to	PART
ijassa-1442	81	8	show	show	VERB
ijassa-1442	81	9	that	that	SCONJ
ijassa-1442	81	10	it	it	PRON
ijassa-1442	81	11	is	be	AUX
ijassa-1442	81	12	possible	possible	ADJ
ijassa-1442	81	13	to	to	PART
ijassa-1442	81	14	maintain	maintain	VERB
ijassa-1442	81	15	good	good	ADJ
ijassa-1442	81	16	predictive	predictive	ADJ
ijassa-1442	81	17	accuracy	accuracy	NOUN
ijassa-1442	81	18	while	while	SCONJ
ijassa-1442	81	19	still	still	ADV
ijassa-1442	81	20	providing	provide	VERB
ijassa-1442	81	21	a	a	DET
ijassa-1442	81	22	strong	strong	ADJ
ijassa-1442	81	23	guarantee	guarantee	NOUN
ijassa-1442	81	24	for	for	ADP
ijassa-1442	81	25	the	the	DET
ijassa-1442	81	26	privacy	privacy	NOUN
ijassa-1442	81	27	of	of	ADP
ijassa-1442	81	28	individuals	individual	NOUN
ijassa-1442	81	29	'	'	PART
ijassa-1442	81	30	data	datum	NOUN
ijassa-1442	81	31	.	.	PUNCT
ijassa-1442	82	1	their	their	PRON
ijassa-1442	82	2	paper	paper	NOUN
ijassa-1442	82	3	is	be	AUX
ijassa-1442	82	4	structured	structure	VERB
ijassa-1442	82	5	around	around	ADP
ijassa-1442	82	6	the	the	DET
ijassa-1442	82	7	concept	concept	NOUN
ijassa-1442	82	8	of	of	ADP
ijassa-1442	82	9	differential	differential	ADJ
ijassa-1442	82	10	privacy	privacy	NOUN
ijassa-1442	82	11	,	,	PUNCT
ijassa-1442	82	12	which	which	PRON
ijassa-1442	82	13	is	be	AUX
ijassa-1442	82	14	a	a	DET
ijassa-1442	82	15	mathematical	mathematical	ADJ
ijassa-1442	82	16	framework	framework	NOUN
ijassa-1442	82	17	for	for	ADP
ijassa-1442	82	18	protecting	protect	VERB
ijassa-1442	82	19	the	the	DET
ijassa-1442	82	20	privacy	privacy	NOUN
ijassa-1442	82	21	of	of	ADP
ijassa-1442	82	22	individuals	individual	NOUN
ijassa-1442	82	23	'	'	PART
ijassa-1442	82	24	data	datum	NOUN
ijassa-1442	82	25	by	by	ADP
ijassa-1442	82	26	adding	add	VERB
ijassa-1442	82	27	noise	noise	NOUN
ijassa-1442	82	28	to	to	ADP
ijassa-1442	82	29	the	the	DET
ijassa-1442	82	30	data	datum	NOUN
ijassa-1442	82	31	.	.	PUNCT
ijassa-1442	83	1	in	in	ADP
ijassa-1442	83	2	[	[	X
ijassa-1442	83	3	16	16	NUM
ijassa-1442	83	4	]	]	PUNCT
ijassa-1442	83	5	authors	author	NOUN
ijassa-1442	83	6	introduce	introduce	VERB
ijassa-1442	83	7	a	a	DET
ijassa-1442	83	8	differentially	differentially	ADV
ijassa-1442	83	9	private	private	ADJ
ijassa-1442	83	10	(	(	PUNCT
ijassa-1442	83	11	dp	dp	NOUN
ijassa-1442	83	12	)	)	PUNCT
ijassa-1442	83	13	neural	neural	ADJ
ijassa-1442	83	14	representation	representation	NOUN
ijassa-1442	83	15	framework	framework	NOUN
ijassa-1442	83	16	that	that	PRON
ijassa-1442	83	17	safeguards	safeguard	VERB
ijassa-1442	83	18	user	user	NOUN
ijassa-1442	83	19	privacy	privacy	NOUN
ijassa-1442	83	20	during	during	ADP
ijassa-1442	83	21	network	network	NOUN
ijassa-1442	83	22	computations	computation	NOUN
ijassa-1442	83	23	,	,	PUNCT
ijassa-1442	83	24	using	use	VERB
ijassa-1442	83	25	a	a	DET
ijassa-1442	83	26	dp	dp	NOUN
ijassa-1442	83	27	noise	noise	NOUN
ijassa-1442	83	28	layer	layer	NOUN
ijassa-1442	83	29	and	and	CCONJ
ijassa-1442	83	30	robust	robust	ADJ
ijassa-1442	83	31	training	training	NOUN
ijassa-1442	83	32	algorithm	algorithm	NOUN
ijassa-1442	83	33	while	while	SCONJ
ijassa-1442	83	34	maintaining	maintain	VERB
ijassa-1442	83	35	performance	performance	NOUN
ijassa-1442	83	36	.	.	PUNCT
ijassa-1442	84	1	the	the	DET
ijassa-1442	84	2	framework	framework	NOUN
ijassa-1442	84	3	offers	offer	VERB
ijassa-1442	84	4	formal	formal	ADJ
ijassa-1442	84	5	privacy	privacy	NOUN
ijassa-1442	84	6	guarantees	guarantee	NOUN
ijassa-1442	84	7	through	through	ADP
ijassa-1442	84	8	sensitivity	sensitivity	NOUN
ijassa-1442	84	9	-	-	PUNCT
ijassa-1442	84	10	based	base	VERB
ijassa-1442	84	11	noise	noise	NOUN
ijassa-1442	84	12	injection	injection	NOUN
ijassa-1442	84	13	.	.	PUNCT
ijassa-1442	85	1	some	some	DET
ijassa-1442	85	2	other	other	ADJ
ijassa-1442	85	3	papers	paper	NOUN
ijassa-1442	85	4	[	[	X
ijassa-1442	85	5	28	28	NUM
ijassa-1442	85	6	,	,	PUNCT
ijassa-1442	85	7	26	26	NUM
ijassa-1442	85	8	,	,	PUNCT
ijassa-1442	85	9	2	2	NUM
ijassa-1442	85	10	,	,	PUNCT
ijassa-1442	85	11	1	1	NUM
ijassa-1442	85	12	]	]	PUNCT
ijassa-1442	85	13	also	also	ADV
ijassa-1442	85	14	learn	learn	VERB
ijassa-1442	85	15	how	how	SCONJ
ijassa-1442	85	16	privacy	privacy	NOUN
ijassa-1442	85	17	affects	affect	VERB
ijassa-1442	85	18	accuracy	accuracy	NOUN
ijassa-1442	85	19	in	in	ADP
ijassa-1442	85	20	different	different	ADJ
ijassa-1442	85	21	models	model	NOUN
ijassa-1442	85	22	.	.	PUNCT
ijassa-1442	86	1	the	the	DET
ijassa-1442	86	2	paper	paper	NOUN
ijassa-1442	86	3	[	[	X
ijassa-1442	86	4	28	28	NUM
ijassa-1442	86	5	]	]	PUNCT
ijassa-1442	86	6	proposes	propose	VERB
ijassa-1442	86	7	a	a	DET
ijassa-1442	86	8	new	new	ADJ
ijassa-1442	86	9	type	type	NOUN
ijassa-1442	86	10	of	of	ADP
ijassa-1442	86	11	generative	generative	ADJ
ijassa-1442	86	12	adversarial	adversarial	ADJ
ijassa-1442	86	13	network	network	NOUN
ijassa-1442	86	14	(	(	PUNCT
ijassa-1442	86	15	gan	gan	PROPN
ijassa-1442	86	16	)	)	PUNCT
ijassa-1442	86	17	called	call	VERB
ijassa-1442	86	18	differentially	differentially	ADV
ijassa-1442	86	19	private	private	ADJ
ijassa-1442	86	20	generative	generative	ADJ
ijassa-1442	86	21	adversarial	adversarial	ADJ
ijassa-1442	86	22	network	network	NOUN
ijassa-1442	86	23	balancing	balancing	NOUN
ijassa-1442	86	24	accuracy	accuracy	NOUN
ijassa-1442	86	25	,	,	PUNCT
ijassa-1442	86	26	fairness	fairness	NOUN
ijassa-1442	86	27	and	and	CCONJ
ijassa-1442	86	28	privacy	privacy	NOUN
ijassa-1442	86	29	in	in	ADP
ijassa-1442	86	30	machine	machine	NOUN
ijassa-1442	86	31	learning	learning	NOUN
ijassa-1442	86	32	…	…	PUNCT
ijassa-1442	86	33	43	43	NUM
ijassa-1442	86	34	copyright	copyright	NOUN
ijassa-1442	86	35	©	©	PROPN
ijassa-1442	86	36	2023	2023	NUM
ijassa-1442	86	37	assa	assa	NOUN
ijassa-1442	86	38	.	.	PUNCT
ijassa-1442	87	1	adv	adv	PROPN
ijassa-1442	87	2	.	.	PUNCT
ijassa-1442	88	1	in	in	ADP
ijassa-1442	88	2	systems	system	NOUN
ijassa-1442	88	3	science	science	NOUN
ijassa-1442	88	4	and	and	CCONJ
ijassa-1442	88	5	appl	appl	NOUN
ijassa-1442	88	6	.	.	PUNCT
ijassa-1442	89	1	(	(	PUNCT
ijassa-1442	89	2	2023	2023	NUM
ijassa-1442	89	3	)	)	PUNCT
ijassa-1442	89	4	(	(	PUNCT
ijassa-1442	89	5	dpgan	dpgan	NOUN
ijassa-1442	89	6	)	)	PUNCT
ijassa-1442	89	7	that	that	PRON
ijassa-1442	89	8	addresses	address	VERB
ijassa-1442	89	9	the	the	DET
ijassa-1442	89	10	issue	issue	NOUN
ijassa-1442	89	11	of	of	ADP
ijassa-1442	89	12	privacy	privacy	NOUN
ijassa-1442	89	13	protection	protection	NOUN
ijassa-1442	89	14	in	in	ADP
ijassa-1442	89	15	training	training	NOUN
ijassa-1442	89	16	data	datum	NOUN
ijassa-1442	89	17	.	.	PUNCT
ijassa-1442	90	1	the	the	DET
ijassa-1442	90	2	dpgan	dpgan	NOUN
ijassa-1442	90	3	adds	add	VERB
ijassa-1442	90	4	carefully	carefully	ADV
ijassa-1442	90	5	designed	design	VERB
ijassa-1442	90	6	noise	noise	NOUN
ijassa-1442	90	7	to	to	ADP
ijassa-1442	90	8	gradients	gradient	NOUN
ijassa-1442	90	9	during	during	ADP
ijassa-1442	90	10	the	the	DET
ijassa-1442	90	11	learning	learning	NOUN
ijassa-1442	90	12	process	process	NOUN
ijassa-1442	90	13	to	to	PART
ijassa-1442	90	14	provide	provide	VERB
ijassa-1442	90	15	differential	differential	ADJ
ijassa-1442	90	16	privacy	privacy	NOUN
ijassa-1442	90	17	,	,	PUNCT
ijassa-1442	90	18	with	with	ADP
ijassa-1442	90	19	a	a	DET
ijassa-1442	90	20	proof	proof	NOUN
ijassa-1442	90	21	of	of	ADP
ijassa-1442	90	22	privacy	privacy	NOUN
ijassa-1442	90	23	guarantee	guarantee	NOUN
ijassa-1442	90	24	and	and	CCONJ
ijassa-1442	90	25	empirical	empirical	ADJ
ijassa-1442	90	26	evidence	evidence	NOUN
ijassa-1442	90	27	to	to	PART
ijassa-1442	90	28	support	support	VERB
ijassa-1442	90	29	its	its	PRON
ijassa-1442	90	30	analysis	analysis	NOUN
ijassa-1442	90	31	.	.	PUNCT
ijassa-1442	91	1	another	another	DET
ijassa-1442	91	2	paper	paper	NOUN
ijassa-1442	92	1	[	[	X
ijassa-1442	92	2	26	26	NUM
ijassa-1442	92	3	]	]	PUNCT
ijassa-1442	92	4	compares	compare	VERB
ijassa-1442	92	5	the	the	DET
ijassa-1442	92	6	fairness	fairness	NOUN
ijassa-1442	92	7	implications	implication	NOUN
ijassa-1442	92	8	of	of	ADP
ijassa-1442	92	9	two	two	NUM
ijassa-1442	92	10	differentially	differentially	ADV
ijassa-1442	92	11	private	private	ADJ
ijassa-1442	92	12	deep	deep	ADJ
ijassa-1442	92	13	learning	learning	NOUN
ijassa-1442	92	14	algorithms	algorithm	NOUN
ijassa-1442	92	15	,	,	PUNCT
ijassa-1442	92	16	dp	dp	NOUN
ijassa-1442	92	17	-	-	PUNCT
ijassa-1442	92	18	sgd	sgd	ADJ
ijassa-1442	92	19	and	and	CCONJ
ijassa-1442	92	20	pate	pate	NOUN
ijassa-1442	92	21	,	,	PUNCT
ijassa-1442	92	22	and	and	CCONJ
ijassa-1442	92	23	finds	find	VERB
ijassa-1442	92	24	that	that	DET
ijassa-1442	92	25	pate	pate	NOUN
ijassa-1442	92	26	has	have	VERB
ijassa-1442	92	27	higher	high	ADJ
ijassa-1442	92	28	utility	utility	NOUN
ijassa-1442	92	29	on	on	ADP
ijassa-1442	92	30	underrepresented	underrepresented	ADJ
ijassa-1442	92	31	groups	group	NOUN
ijassa-1442	92	32	in	in	ADP
ijassa-1442	92	33	imbalanced	imbalanced	ADJ
ijassa-1442	92	34	datasets	dataset	NOUN
ijassa-1442	92	35	.	.	PUNCT
ijassa-1442	93	1	the	the	DET
ijassa-1442	93	2	impact	impact	NOUN
ijassa-1442	93	3	of	of	ADP
ijassa-1442	93	4	differential	differential	ADJ
ijassa-1442	93	5	privacy	privacy	NOUN
ijassa-1442	93	6	on	on	ADP
ijassa-1442	93	7	the	the	DET
ijassa-1442	93	8	accuracy	accuracy	NOUN
ijassa-1442	93	9	of	of	ADP
ijassa-1442	93	10	machine	machine	NOUN
ijassa-1442	93	11	learning	learning	NOUN
ijassa-1442	93	12	models	model	NOUN
ijassa-1442	93	13	is	be	AUX
ijassa-1442	93	14	also	also	ADV
ijassa-1442	93	15	examined	examine	VERB
ijassa-1442	93	16	[	[	PUNCT
ijassa-1442	93	17	2	2	NUM
ijassa-1442	93	18	]	]	PUNCT
ijassa-1442	93	19	,	,	PUNCT
ijassa-1442	93	20	and	and	CCONJ
ijassa-1442	93	21	it	it	PRON
ijassa-1442	93	22	is	be	AUX
ijassa-1442	93	23	found	find	VERB
ijassa-1442	93	24	that	that	SCONJ
ijassa-1442	93	25	the	the	DET
ijassa-1442	93	26	reduction	reduction	NOUN
ijassa-1442	93	27	in	in	ADP
ijassa-1442	93	28	accuracy	accuracy	NOUN
ijassa-1442	93	29	brought	bring	VERB
ijassa-1442	93	30	about	about	ADP
ijassa-1442	93	31	by	by	ADP
ijassa-1442	93	32	dp	dp	NOUN
ijassa-1442	93	33	disproportionately	disproportionately	ADV
ijassa-1442	93	34	affects	affect	VERB
ijassa-1442	93	35	underrepresented	underrepresented	ADJ
ijassa-1442	93	36	subgroups	subgroup	NOUN
ijassa-1442	93	37	and	and	CCONJ
ijassa-1442	93	38	subgroups	subgroup	NOUN
ijassa-1442	93	39	with	with	ADP
ijassa-1442	93	40	more	more	ADJ
ijassa-1442	93	41	complex	complex	ADJ
ijassa-1442	93	42	data	datum	NOUN
ijassa-1442	93	43	.	.	PUNCT
ijassa-1442	94	1	the	the	DET
ijassa-1442	94	2	authors	author	NOUN
ijassa-1442	94	3	of	of	ADP
ijassa-1442	94	4	next	next	ADJ
ijassa-1442	94	5	paper	paper	NOUN
ijassa-1442	94	6	[	[	X
ijassa-1442	94	7	1	1	X
ijassa-1442	94	8	]	]	X
ijassa-1442	94	9	present	present	ADJ
ijassa-1442	94	10	new	new	ADJ
ijassa-1442	94	11	algorithmic	algorithmic	ADJ
ijassa-1442	94	12	techniques	technique	NOUN
ijassa-1442	94	13	and	and	CCONJ
ijassa-1442	94	14	a	a	DET
ijassa-1442	94	15	refined	refined	ADJ
ijassa-1442	94	16	analysis	analysis	NOUN
ijassa-1442	94	17	of	of	ADP
ijassa-1442	94	18	privacy	privacy	NOUN
ijassa-1442	94	19	costs	cost	NOUN
ijassa-1442	94	20	to	to	PART
ijassa-1442	94	21	train	train	VERB
ijassa-1442	94	22	deep	deep	ADJ
ijassa-1442	94	23	neural	neural	ADJ
ijassa-1442	94	24	networks	network	NOUN
ijassa-1442	94	25	while	while	SCONJ
ijassa-1442	94	26	ensuring	ensure	VERB
ijassa-1442	94	27	privacy	privacy	NOUN
ijassa-1442	94	28	.	.	PUNCT
ijassa-1442	95	1	the	the	DET
ijassa-1442	95	2	solution	solution	NOUN
ijassa-1442	95	3	is	be	AUX
ijassa-1442	95	4	evaluated	evaluate	VERB
ijassa-1442	95	5	on	on	ADP
ijassa-1442	95	6	standard	standard	ADJ
ijassa-1442	95	7	image	image	NOUN
ijassa-1442	95	8	classification	classification	NOUN
ijassa-1442	95	9	tasks	task	NOUN
ijassa-1442	95	10	(	(	PUNCT
ijassa-1442	95	11	mnist	mnist	NOUN
ijassa-1442	95	12	and	and	CCONJ
ijassa-1442	95	13	cifar-10	cifar-10	PROPN
ijassa-1442	95	14	)	)	PUNCT
ijassa-1442	95	15	and	and	CCONJ
ijassa-1442	95	16	demonstrates	demonstrate	VERB
ijassa-1442	95	17	the	the	DET
ijassa-1442	95	18	feasibility	feasibility	NOUN
ijassa-1442	95	19	of	of	ADP
ijassa-1442	95	20	the	the	DET
ijassa-1442	95	21	approach	approach	NOUN
ijassa-1442	95	22	against	against	ADP
ijassa-1442	95	23	a	a	DET
ijassa-1442	95	24	strong	strong	ADJ
ijassa-1442	95	25	adversary	adversary	NOUN
ijassa-1442	95	26	who	who	PRON
ijassa-1442	95	27	has	have	VERB
ijassa-1442	95	28	full	full	ADJ
ijassa-1442	95	29	knowledge	knowledge	NOUN
ijassa-1442	95	30	of	of	ADP
ijassa-1442	95	31	the	the	DET
ijassa-1442	95	32	training	training	NOUN
ijassa-1442	95	33	mechanism	mechanism	NOUN
ijassa-1442	95	34	and	and	CCONJ
ijassa-1442	95	35	access	access	NOUN
ijassa-1442	95	36	to	to	ADP
ijassa-1442	95	37	the	the	DET
ijassa-1442	95	38	model	model	NOUN
ijassa-1442	95	39	's	's	PART
ijassa-1442	95	40	parameters	parameter	NOUN
ijassa-1442	95	41	.	.	PUNCT
ijassa-1442	96	1	there	there	PRON
ijassa-1442	96	2	are	be	VERB
ijassa-1442	96	3	some	some	DET
ijassa-1442	96	4	papers	paper	NOUN
ijassa-1442	96	5	,	,	PUNCT
ijassa-1442	96	6	which	which	PRON
ijassa-1442	96	7	explore	explore	VERB
ijassa-1442	96	8	the	the	DET
ijassa-1442	96	9	effect	effect	NOUN
ijassa-1442	96	10	of	of	ADP
ijassa-1442	96	11	privacy	privacy	NOUN
ijassa-1442	96	12	introduction	introduction	NOUN
ijassa-1442	96	13	on	on	ADP
ijassa-1442	96	14	fairness	fairness	NOUN
ijassa-1442	96	15	.	.	PUNCT
ijassa-1442	97	1	the	the	DET
ijassa-1442	97	2	first	first	ADJ
ijassa-1442	97	3	paper	paper	NOUN
ijassa-1442	98	1	[	[	X
ijassa-1442	98	2	24	24	NUM
ijassa-1442	98	3	]	]	PUNCT
ijassa-1442	98	4	explores	explore	VERB
ijassa-1442	98	5	the	the	DET
ijassa-1442	98	6	impact	impact	NOUN
ijassa-1442	98	7	of	of	ADP
ijassa-1442	98	8	differential	differential	ADJ
ijassa-1442	98	9	privacy	privacy	NOUN
ijassa-1442	98	10	algorithms	algorithm	NOUN
ijassa-1442	98	11	on	on	ADP
ijassa-1442	98	12	the	the	DET
ijassa-1442	98	13	fairness	fairness	NOUN
ijassa-1442	98	14	of	of	ADP
ijassa-1442	98	15	machine	machine	NOUN
ijassa-1442	98	16	learning	learning	NOUN
ijassa-1442	98	17	systems	system	NOUN
ijassa-1442	98	18	.	.	PUNCT
ijassa-1442	99	1	it	it	PRON
ijassa-1442	99	2	focuses	focus	VERB
ijassa-1442	99	3	on	on	ADP
ijassa-1442	99	4	two	two	NUM
ijassa-1442	99	5	specific	specific	ADJ
ijassa-1442	99	6	differential	differential	NOUN
ijassa-1442	99	7	privacy	privacy	NOUN
ijassa-1442	99	8	methods	method	NOUN
ijassa-1442	99	9	and	and	CCONJ
ijassa-1442	99	10	analyses	analyse	VERB
ijassa-1442	99	11	the	the	DET
ijassa-1442	99	12	reasons	reason	NOUN
ijassa-1442	99	13	for	for	ADP
ijassa-1442	99	14	the	the	DET
ijassa-1442	99	15	disparities	disparity	NOUN
ijassa-1442	99	16	that	that	PRON
ijassa-1442	99	17	arise	arise	VERB
ijassa-1442	99	18	among	among	ADP
ijassa-1442	99	19	different	different	ADJ
ijassa-1442	99	20	groups	group	NOUN
ijassa-1442	99	21	of	of	ADP
ijassa-1442	99	22	individuals	individual	NOUN
ijassa-1442	99	23	in	in	ADP
ijassa-1442	99	24	these	these	DET
ijassa-1442	99	25	methods	method	NOUN
ijassa-1442	99	26	.	.	PUNCT
ijassa-1442	100	1	the	the	DET
ijassa-1442	100	2	paper	paper	NOUN
ijassa-1442	100	3	proposes	propose	VERB
ijassa-1442	100	4	guidelines	guideline	NOUN
ijassa-1442	100	5	to	to	PART
ijassa-1442	100	6	mitigate	mitigate	VERB
ijassa-1442	100	7	the	the	DET
ijassa-1442	100	8	unfair	unfair	ADJ
ijassa-1442	100	9	impacts	impact	NOUN
ijassa-1442	100	10	and	and	CCONJ
ijassa-1442	100	11	contributes	contribute	VERB
ijassa-1442	100	12	to	to	ADP
ijassa-1442	100	13	the	the	DET
ijassa-1442	100	14	growing	grow	VERB
ijassa-1442	100	15	research	research	NOUN
ijassa-1442	100	16	at	at	ADP
ijassa-1442	100	17	the	the	DET
ijassa-1442	100	18	interface	interface	NOUN
ijassa-1442	100	19	between	between	ADP
ijassa-1442	100	20	differential	differential	NOUN
ijassa-1442	100	21	privacy	privacy	NOUN
ijassa-1442	100	22	and	and	CCONJ
ijassa-1442	100	23	fairness	fairness	NOUN
ijassa-1442	100	24	.	.	PUNCT
ijassa-1442	101	1	the	the	DET
ijassa-1442	101	2	second	second	ADJ
ijassa-1442	101	3	paper	paper	NOUN
ijassa-1442	101	4	[	[	X
ijassa-1442	101	5	25	25	NUM
ijassa-1442	101	6	]	]	PUNCT
ijassa-1442	101	7	considers	consider	VERB
ijassa-1442	101	8	importance	importance	NOUN
ijassa-1442	101	9	of	of	ADP
ijassa-1442	101	10	ensuring	ensure	VERB
ijassa-1442	101	11	fairness	fairness	NOUN
ijassa-1442	101	12	in	in	ADP
ijassa-1442	101	13	machine	machine	NOUN
ijassa-1442	101	14	learning	learning	NOUN
ijassa-1442	101	15	systems	system	NOUN
ijassa-1442	101	16	,	,	PUNCT
ijassa-1442	101	17	specifically	specifically	ADV
ijassa-1442	101	18	in	in	ADP
ijassa-1442	101	19	the	the	DET
ijassa-1442	101	20	context	context	NOUN
ijassa-1442	101	21	of	of	ADP
ijassa-1442	101	22	decisions	decision	NOUN
ijassa-1442	101	23	that	that	PRON
ijassa-1442	101	24	affect	affect	VERB
ijassa-1442	101	25	individuals	individual	NOUN
ijassa-1442	101	26	,	,	PUNCT
ijassa-1442	101	27	such	such	ADJ
ijassa-1442	101	28	as	as	ADP
ijassa-1442	101	29	criminal	criminal	ADJ
ijassa-1442	101	30	assessment	assessment	NOUN
ijassa-1442	101	31	and	and	CCONJ
ijassa-1442	101	32	hiring	hiring	NOUN
ijassa-1442	101	33	.	.	PUNCT
ijassa-1442	102	1	the	the	DET
ijassa-1442	102	2	text	text	NOUN
ijassa-1442	102	3	highlights	highlight	VERB
ijassa-1442	102	4	the	the	DET
ijassa-1442	102	5	trade	trade	NOUN
ijassa-1442	102	6	-	-	PUNCT
ijassa-1442	102	7	off	off	NOUN
ijassa-1442	102	8	between	between	ADP
ijassa-1442	102	9	model	model	NOUN
ijassa-1442	102	10	accuracy	accuracy	NOUN
ijassa-1442	102	11	and	and	CCONJ
ijassa-1442	102	12	fairness	fairness	NOUN
ijassa-1442	102	13	and	and	CCONJ
ijassa-1442	102	14	the	the	DET
ijassa-1442	102	15	importance	importance	NOUN
ijassa-1442	102	16	of	of	ADP
ijassa-1442	102	17	considering	consider	VERB
ijassa-1442	102	18	sensitive	sensitive	ADJ
ijassa-1442	102	19	attributes	attribute	NOUN
ijassa-1442	102	20	in	in	ADP
ijassa-1442	102	21	learning	learn	VERB
ijassa-1442	102	22	tasks	task	NOUN
ijassa-1442	102	23	to	to	PART
ijassa-1442	102	24	ensure	ensure	VERB
ijassa-1442	102	25	non	non	ADJ
ijassa-1442	102	26	-	-	NOUN
ijassa-1442	102	27	discrimination	discrimination	NOUN
ijassa-1442	102	28	.	.	PUNCT
ijassa-1442	103	1	in	in	ADP
ijassa-1442	103	2	this	this	DET
ijassa-1442	103	3	paper	paper	NOUN
ijassa-1442	103	4	,	,	PUNCT
ijassa-1442	103	5	the	the	DET
ijassa-1442	103	6	focus	focus	NOUN
ijassa-1442	103	7	is	be	AUX
ijassa-1442	103	8	on	on	ADP
ijassa-1442	103	9	the	the	DET
ijassa-1442	103	10	integration	integration	NOUN
ijassa-1442	103	11	of	of	ADP
ijassa-1442	103	12	algorithmic	algorithmic	ADJ
ijassa-1442	103	13	fairness	fairness	NOUN
ijassa-1442	103	14	and	and	CCONJ
ijassa-1442	103	15	differential	differential	NOUN
ijassa-1442	103	16	privacy	privacy	NOUN
ijassa-1442	103	17	in	in	ADP
ijassa-1442	103	18	the	the	DET
ijassa-1442	103	19	training	training	NOUN
ijassa-1442	103	20	process	process	NOUN
ijassa-1442	103	21	of	of	ADP
ijassa-1442	103	22	machine	machine	NOUN
ijassa-1442	103	23	learning	learning	NOUN
ijassa-1442	103	24	models	model	NOUN
ijassa-1442	103	25	.	.	PUNCT
ijassa-1442	104	1	differential	differential	PROPN
ijassa-1442	104	2	privacy	privacy	NOUN
ijassa-1442	104	3	,	,	PUNCT
ijassa-1442	104	4	which	which	PRON
ijassa-1442	104	5	is	be	AUX
ijassa-1442	104	6	a	a	DET
ijassa-1442	104	7	mathematical	mathematical	ADJ
ijassa-1442	104	8	framework	framework	NOUN
ijassa-1442	104	9	for	for	ADP
ijassa-1442	104	10	the	the	DET
ijassa-1442	104	11	protection	protection	NOUN
ijassa-1442	104	12	of	of	ADP
ijassa-1442	104	13	the	the	DET
ijassa-1442	104	14	privacy	privacy	NOUN
ijassa-1442	104	15	of	of	ADP
ijassa-1442	104	16	individuals	individual	NOUN
ijassa-1442	104	17	'	'	PART
ijassa-1442	104	18	data	datum	NOUN
ijassa-1442	104	19	by	by	ADP
ijassa-1442	104	20	the	the	DET
ijassa-1442	104	21	addition	addition	NOUN
ijassa-1442	104	22	of	of	ADP
ijassa-1442	104	23	noise	noise	NOUN
ijassa-1442	104	24	to	to	ADP
ijassa-1442	104	25	the	the	DET
ijassa-1442	104	26	data	datum	NOUN
ijassa-1442	104	27	,	,	PUNCT
ijassa-1442	104	28	is	be	AUX
ijassa-1442	104	29	utilized	utilize	VERB
ijassa-1442	104	30	as	as	ADP
ijassa-1442	104	31	the	the	DET
ijassa-1442	104	32	main	main	ADJ
ijassa-1442	104	33	method	method	NOUN
ijassa-1442	104	34	for	for	ADP
ijassa-1442	104	35	privacy	privacy	NOUN
ijassa-1442	104	36	preservation	preservation	NOUN
ijassa-1442	104	37	.	.	PUNCT
ijassa-1442	105	1	the	the	DET
ijassa-1442	105	2	laftr	laftr	ADJ
ijassa-1442	105	3	model	model	NOUN
ijassa-1442	105	4	,	,	PUNCT
ijassa-1442	105	5	designed	design	VERB
ijassa-1442	105	6	to	to	PART
ijassa-1442	105	7	provide	provide	VERB
ijassa-1442	105	8	a	a	DET
ijassa-1442	105	9	fair	fair	ADJ
ijassa-1442	105	10	data	datum	NOUN
ijassa-1442	105	11	representation	representation	NOUN
ijassa-1442	105	12	while	while	SCONJ
ijassa-1442	105	13	maintaining	maintain	VERB
ijassa-1442	105	14	good	good	ADJ
ijassa-1442	105	15	predictive	predictive	ADJ
ijassa-1442	105	16	accuracy	accuracy	NOUN
ijassa-1442	105	17	,	,	PUNCT
ijassa-1442	105	18	is	be	AUX
ijassa-1442	105	19	evaluated	evaluate	VERB
ijassa-1442	105	20	.	.	PUNCT
ijassa-1442	106	1	the	the	DET
ijassa-1442	106	2	performance	performance	NOUN
ijassa-1442	106	3	of	of	ADP
ijassa-1442	106	4	the	the	DET
ijassa-1442	106	5	laftr	laftr	ADJ
ijassa-1442	106	6	model	model	NOUN
ijassa-1442	106	7	is	be	AUX
ijassa-1442	106	8	assessed	assess	VERB
ijassa-1442	106	9	and	and	CCONJ
ijassa-1442	106	10	the	the	DET
ijassa-1442	106	11	fairness	fairness	NOUN
ijassa-1442	106	12	and	and	CCONJ
ijassa-1442	106	13	accuracy	accuracy	NOUN
ijassa-1442	106	14	indicators	indicator	NOUN
ijassa-1442	106	15	are	be	AUX
ijassa-1442	106	16	evaluated	evaluate	VERB
ijassa-1442	106	17	in	in	ADP
ijassa-1442	106	18	a	a	DET
ijassa-1442	106	19	classification	classification	NOUN
ijassa-1442	106	20	problem	problem	NOUN
ijassa-1442	106	21	,	,	PUNCT
ijassa-1442	106	22	which	which	PRON
ijassa-1442	106	23	is	be	AUX
ijassa-1442	106	24	a	a	DET
ijassa-1442	106	25	common	common	ADJ
ijassa-1442	106	26	application	application	NOUN
ijassa-1442	106	27	in	in	ADP
ijassa-1442	106	28	machine	machine	NOUN
ijassa-1442	106	29	learning	learning	NOUN
ijassa-1442	106	30	.	.	PUNCT
ijassa-1442	107	1	machine	machine	NOUN
ijassa-1442	107	2	learning	learning	NOUN
ijassa-1442	107	3	bias	bias	NOUN
ijassa-1442	107	4	refers	refer	VERB
ijassa-1442	107	5	to	to	ADP
ijassa-1442	107	6	a	a	DET
ijassa-1442	107	7	systematic	systematic	ADJ
ijassa-1442	107	8	error	error	NOUN
ijassa-1442	107	9	that	that	PRON
ijassa-1442	107	10	occurs	occur	VERB
ijassa-1442	107	11	in	in	ADP
ijassa-1442	107	12	the	the	DET
ijassa-1442	107	13	results	result	NOUN
ijassa-1442	107	14	due	due	ADP
ijassa-1442	107	15	to	to	ADP
ijassa-1442	107	16	incorrect	incorrect	ADJ
ijassa-1442	107	17	assumptions	assumption	NOUN
ijassa-1442	107	18	.	.	PUNCT
ijassa-1442	108	1	the	the	DET
ijassa-1442	108	2	objective	objective	NOUN
ijassa-1442	108	3	of	of	ADP
ijassa-1442	108	4	algorithmic	algorithmic	ADJ
ijassa-1442	108	5	fairness	fairness	NOUN
ijassa-1442	108	6	is	be	AUX
ijassa-1442	108	7	to	to	PART
ijassa-1442	108	8	reduce	reduce	VERB
ijassa-1442	108	9	this	this	DET
ijassa-1442	108	10	bias	bias	NOUN
ijassa-1442	108	11	.	.	PUNCT
ijassa-1442	109	1	this	this	PRON
ijassa-1442	109	2	is	be	AUX
ijassa-1442	109	3	achieved	achieve	VERB
ijassa-1442	109	4	through	through	ADP
ijassa-1442	109	5	three	three	NUM
ijassa-1442	109	6	main	main	ADJ
ijassa-1442	109	7	categories	category	NOUN
ijassa-1442	109	8	of	of	ADP
ijassa-1442	109	9	algorithms	algorithm	NOUN
ijassa-1442	109	10	:	:	PUNCT
ijassa-1442	109	11	pre	pre	ADJ
ijassa-1442	109	12	-	-	ADJ
ijassa-1442	109	13	processing	processing	ADJ
ijassa-1442	109	14	,	,	PUNCT
ijassa-1442	109	15	in	in	ADP
ijassa-1442	109	16	-	-	PUNCT
ijassa-1442	109	17	processing	processing	NOUN
ijassa-1442	109	18	,	,	PUNCT
ijassa-1442	109	19	and	and	CCONJ
ijassa-1442	109	20	post	post	ADJ
ijassa-1442	109	21	-	-	ADJ
ijassa-1442	109	22	processing	processing	NOUN
ijassa-1442	109	23	.	.	PUNCT
ijassa-1442	110	1	pre	pre	ADJ
ijassa-1442	110	2	-	-	ADJ
ijassa-1442	110	3	processing	processing	ADJ
ijassa-1442	110	4	techniques	technique	NOUN
ijassa-1442	110	5	aim	aim	VERB
ijassa-1442	110	6	to	to	PART
ijassa-1442	110	7	reweight	reweight	ADJ
ijassa-1442	110	8	training	training	NOUN
ijassa-1442	110	9	samples	sample	NOUN
ijassa-1442	110	10	[	[	X
ijassa-1442	110	11	15	15	NUM
ijassa-1442	110	12	]	]	PUNCT
ijassa-1442	110	13	,	,	PUNCT
ijassa-1442	110	14	edit	edit	NOUN
ijassa-1442	110	15	features	feature	NOUN
ijassa-1442	110	16	and	and	CCONJ
ijassa-1442	110	17	labels	label	NOUN
ijassa-1442	110	18	[	[	X
ijassa-1442	110	19	4	4	NUM
ijassa-1442	110	20	]	]	PUNCT
ijassa-1442	110	21	,	,	PUNCT
ijassa-1442	110	22	and	and	CCONJ
ijassa-1442	110	23	resample	resample	ADJ
ijassa-1442	110	24	datasets	dataset	NOUN
ijassa-1442	110	25	[	[	X
ijassa-1442	110	26	5	5	NUM
ijassa-1442	110	27	]	]	PUNCT
ijassa-1442	110	28	.	.	PUNCT
ijassa-1442	111	1	in	in	ADP
ijassa-1442	111	2	contrast	contrast	NOUN
ijassa-1442	111	3	,	,	PUNCT
ijassa-1442	111	4	postprocessing	postprocessing	NOUN
ijassa-1442	111	5	methods	method	NOUN
ijassa-1442	111	6	aim	aim	VERB
ijassa-1442	111	7	to	to	PART
ijassa-1442	111	8	calibrate	calibrate	VERB
ijassa-1442	111	9	predictions	prediction	NOUN
ijassa-1442	111	10	[	[	X
ijassa-1442	111	11	12	12	NUM
ijassa-1442	111	12	,	,	PUNCT
ijassa-1442	111	13	7	7	NUM
ijassa-1442	111	14	]	]	PUNCT
ijassa-1442	111	15	by	by	ADP
ijassa-1442	111	16	adjusting	adjust	VERB
ijassa-1442	111	17	the	the	DET
ijassa-1442	111	18	learned	learn	VERB
ijassa-1442	111	19	predictor	predictor	NOUN
ijassa-1442	111	20	to	to	PART
ijassa-1442	111	21	remove	remove	VERB
ijassa-1442	111	22	discrimination	discrimination	NOUN
ijassa-1442	111	23	based	base	VERB
ijassa-1442	111	24	on	on	ADP
ijassa-1442	111	25	the	the	DET
ijassa-1442	111	26	joint	joint	ADJ
ijassa-1442	111	27	statistics	statistic	NOUN
ijassa-1442	111	28	of	of	ADP
ijassa-1442	111	29	the	the	DET
ijassa-1442	111	30	predictor	predictor	NOUN
ijassa-1442	111	31	,	,	PUNCT
ijassa-1442	111	32	target	target	NOUN
ijassa-1442	111	33	,	,	PUNCT
ijassa-1442	111	34	and	and	CCONJ
ijassa-1442	111	35	protected	protect	VERB
ijassa-1442	111	36	attribute	attribute	NOUN
ijassa-1442	111	37	.	.	PUNCT
ijassa-1442	112	1	in	in	ADP
ijassa-1442	112	2	-	-	PUNCT
ijassa-1442	112	3	processing	processing	NOUN
ijassa-1442	112	4	techniques	technique	NOUN
ijassa-1442	112	5	[	[	X
ijassa-1442	112	6	14	14	NUM
ijassa-1442	112	7	,	,	PUNCT
ijassa-1442	112	8	18	18	NUM
ijassa-1442	112	9	,	,	PUNCT
ijassa-1442	112	10	11	11	NUM
ijassa-1442	112	11	,	,	PUNCT
ijassa-1442	112	12	29	29	NUM
ijassa-1442	112	13	,	,	PUNCT
ijassa-1442	112	14	17	17	NUM
ijassa-1442	112	15	,	,	PUNCT
ijassa-1442	112	16	6	6	NUM
ijassa-1442	112	17	,	,	PUNCT
ijassa-1442	112	18	30	30	NUM
ijassa-1442	112	19	]	]	PUNCT
ijassa-1442	112	20	focus	focus	NOUN
ijassa-1442	112	21	on	on	ADP
ijassa-1442	112	22	removing	remove	VERB
ijassa-1442	112	23	sensitive	sensitive	ADJ
ijassa-1442	112	24	information	information	NOUN
ijassa-1442	112	25	,	,	PUNCT
ijassa-1442	112	26	such	such	ADJ
ijassa-1442	112	27	as	as	ADP
ijassa-1442	112	28	racial	racial	ADJ
ijassa-1442	112	29	or	or	CCONJ
ijassa-1442	112	30	gender	gender	NOUN
ijassa-1442	112	31	group	group	NOUN
ijassa-1442	112	32	,	,	PUNCT
ijassa-1442	112	33	age	age	NOUN
ijassa-1442	112	34	,	,	PUNCT
ijassa-1442	112	35	financial	financial	ADJ
ijassa-1442	112	36	transactions	transaction	NOUN
ijassa-1442	112	37	or	or	CCONJ
ijassa-1442	112	38	tax	tax	NOUN
ijassa-1442	112	39	payments	payment	NOUN
ijassa-1442	112	40	that	that	PRON
ijassa-1442	112	41	may	may	AUX
ijassa-1442	112	42	lead	lead	VERB
ijassa-1442	112	43	to	to	ADP
ijassa-1442	112	44	discrimination	discrimination	NOUN
ijassa-1442	112	45	or	or	CCONJ
ijassa-1442	112	46	bias	bias	NOUN
ijassa-1442	112	47	in	in	ADP
ijassa-1442	112	48	decision	decision	NOUN
ijassa-1442	112	49	making	making	NOUN
ijassa-1442	112	50	,	,	PUNCT
ijassa-1442	112	51	from	from	ADP
ijassa-1442	112	52	the	the	DET
ijassa-1442	112	53	data	datum	NOUN
ijassa-1442	112	54	.	.	PUNCT
ijassa-1442	113	1	there	there	PRON
ijassa-1442	113	2	are	be	VERB
ijassa-1442	113	3	various	various	ADJ
ijassa-1442	113	4	architectures	architecture	NOUN
ijassa-1442	113	5	of	of	ADP
ijassa-1442	113	6	models	model	NOUN
ijassa-1442	113	7	for	for	ADP
ijassa-1442	113	8	realizing	realize	VERB
ijassa-1442	113	9	fair	fair	ADJ
ijassa-1442	113	10	representation	representation	NOUN
ijassa-1442	113	11	in	in	ADP
ijassa-1442	113	12	-	-	PUNCT
ijassa-1442	113	13	processing	processing	NOUN
ijassa-1442	113	14	,	,	PUNCT
ijassa-1442	113	15	such	such	ADJ
ijassa-1442	113	16	as	as	ADP
ijassa-1442	113	17	cfair	cfair	NOUN
ijassa-1442	113	18	[	[	X
ijassa-1442	113	19	29	29	NUM
ijassa-1442	113	20	]	]	PUNCT
ijassa-1442	113	21	,	,	PUNCT
ijassa-1442	113	22	laftr	laftr	ADP
ijassa-1442	113	23	[	[	X
ijassa-1442	113	24	17	17	NUM
ijassa-1442	113	25	]	]	PUNCT
ijassa-1442	113	26	,	,	PUNCT
ijassa-1442	113	27	ffvae	ffvae	VERB
ijassa-1442	113	28	[	[	X
ijassa-1442	113	29	6	6	NUM
ijassa-1442	113	30	]	]	PUNCT
ijassa-1442	113	31	,	,	PUNCT
ijassa-1442	113	32	among	among	ADP
ijassa-1442	113	33	others	other	NOUN
ijassa-1442	113	34	.	.	PUNCT
ijassa-1442	114	1	one	one	NUM
ijassa-1442	114	2	of	of	ADP
ijassa-1442	114	3	the	the	DET
ijassa-1442	114	4	architectures	architecture	NOUN
ijassa-1442	114	5	of	of	ADP
ijassa-1442	114	6	the	the	DET
ijassa-1442	114	7	adversarial	adversarial	ADJ
ijassa-1442	114	8	biasmitigation	biasmitigation	NOUN
ijassa-1442	114	9	model	model	NOUN
ijassa-1442	114	10	consists	consist	VERB
ijassa-1442	114	11	of	of	ADP
ijassa-1442	114	12	an	an	DET
ijassa-1442	114	13	encoder	encoder	NOUN
ijassa-1442	114	14	,	,	PUNCT
ijassa-1442	114	15	adversary	adversary	NOUN
ijassa-1442	114	16	module	module	NOUN
ijassa-1442	114	17	,	,	PUNCT
ijassa-1442	114	18	and	and	CCONJ
ijassa-1442	114	19	classifier	classifier	NOUN
ijassa-1442	114	20	.	.	PUNCT
ijassa-1442	115	1	the	the	DET
ijassa-1442	115	2	encoder	encoder	NOUN
ijassa-1442	115	3	takes	take	VERB
ijassa-1442	115	4	in	in	ADP
ijassa-1442	115	5	the	the	DET
ijassa-1442	115	6	data	datum	NOUN
ijassa-1442	115	7	and	and	CCONJ
ijassa-1442	115	8	considers	consider	VERB
ijassa-1442	115	9	the	the	DET
ijassa-1442	115	10	sensitive	sensitive	ADJ
ijassa-1442	115	11	attribute	attribute	NOUN
ijassa-1442	115	12	while	while	SCONJ
ijassa-1442	115	13	encoding	encode	VERB
ijassa-1442	115	14	the	the	DET
ijassa-1442	115	15	data	datum	NOUN
ijassa-1442	115	16	into	into	ADP
ijassa-1442	115	17	the	the	DET
ijassa-1442	115	18	latent	latent	NOUN
ijassa-1442	115	19	space	space	NOUN
ijassa-1442	115	20	.	.	PUNCT
ijassa-1442	116	1	the	the	DET
ijassa-1442	116	2	adversarial	adversarial	ADJ
ijassa-1442	116	3	training	training	NOUN
ijassa-1442	116	4	setup	setup	NOUN
ijassa-1442	116	5	,	,	PUNCT
ijassa-1442	116	6	using	use	VERB
ijassa-1442	116	7	a	a	DET
ijassa-1442	116	8	gradient	gradient	NOUN
ijassa-1442	116	9	-	-	PUNCT
ijassa-1442	116	10	reversal	reversal	NOUN
ijassa-1442	116	11	layer	layer	NOUN
ijassa-1442	116	12	and	and	CCONJ
ijassa-1442	116	13	an	an	DET
ijassa-1442	116	14	attacker	attacker	NOUN
ijassa-1442	116	15	network	network	NOUN
ijassa-1442	116	16	,	,	PUNCT
ijassa-1442	116	17	to	to	PART
ijassa-1442	116	18	train	train	VERB
ijassa-1442	116	19	a	a	DET
ijassa-1442	116	20	classifier	classifier	NOUN
ijassa-1442	116	21	that	that	PRON
ijassa-1442	116	22	accurately	accurately	ADV
ijassa-1442	116	23	predicts	predict	VERB
ijassa-1442	116	24	main	main	ADJ
ijassa-1442	116	25	task	task	NOUN
ijassa-1442	116	26	labels	label	NOUN
ijassa-1442	116	27	while	while	SCONJ
ijassa-1442	116	28	being	be	AUX
ijassa-1442	116	29	oblivious	oblivious	ADJ
ijassa-1442	116	30	to	to	PART
ijassa-1442	116	31	protected	protect	VERB
ijassa-1442	116	32	attributes	attribute	NOUN
ijassa-1442	116	33	[	[	X
ijassa-1442	116	34	10	10	NUM
ijassa-1442	116	35	]	]	PUNCT
ijassa-1442	116	36	.	.	PUNCT
ijassa-1442	117	1	finally	finally	ADV
ijassa-1442	117	2	,	,	PUNCT
ijassa-1442	117	3	the	the	DET
ijassa-1442	117	4	data	datum	NOUN
ijassa-1442	117	5	from	from	ADP
ijassa-1442	117	6	the	the	DET
ijassa-1442	117	7	preserved	preserve	VERB
ijassa-1442	117	8	latent	latent	NOUN
ijassa-1442	117	9	space	space	NOUN
ijassa-1442	117	10	is	be	AUX
ijassa-1442	117	11	passed	pass	VERB
ijassa-1442	117	12	on	on	ADP
ijassa-1442	117	13	to	to	ADP
ijassa-1442	117	14	the	the	DET
ijassa-1442	117	15	classifier	classifier	NOUN
ijassa-1442	117	16	,	,	PUNCT
ijassa-1442	117	17	which	which	PRON
ijassa-1442	117	18	has	have	VERB
ijassa-1442	117	19	an	an	DET
ijassa-1442	117	20	integrated	integrated	ADJ
ijassa-1442	117	21	architecture	architecture	NOUN
ijassa-1442	117	22	.	.	PUNCT
ijassa-1442	118	1	this	this	DET
ijassa-1442	118	2	architecture	architecture	NOUN
ijassa-1442	118	3	is	be	AUX
ijassa-1442	118	4	further	far	ADV
ijassa-1442	118	5	described	describe	VERB
ijassa-1442	118	6	in	in	ADP
ijassa-1442	118	7	[	[	X
ijassa-1442	118	8	17	17	NUM
ijassa-1442	118	9	]	]	PUNCT
ijassa-1442	118	10	.	.	PUNCT
ijassa-1442	119	1	in	in	ADP
ijassa-1442	119	2	this	this	DET
ijassa-1442	119	3	work	work	NOUN
ijassa-1442	119	4	,	,	PUNCT
ijassa-1442	119	5	the	the	DET
ijassa-1442	119	6	focus	focus	NOUN
ijassa-1442	119	7	is	be	AUX
ijassa-1442	119	8	on	on	ADP
ijassa-1442	119	9	using	use	VERB
ijassa-1442	119	10	the	the	DET
ijassa-1442	119	11	laftr	laftr	ADJ
ijassa-1442	119	12	model	model	NOUN
ijassa-1442	119	13	to	to	PART
ijassa-1442	119	14	generate	generate	VERB
ijassa-1442	119	15	data	datum	NOUN
ijassa-1442	119	16	for	for	ADP
ijassa-1442	119	17	a	a	DET
ijassa-1442	119	18	third	third	ADJ
ijassa-1442	119	19	-	-	PUNCT
ijassa-1442	119	20	party	party	NOUN
ijassa-1442	119	21	classifier	classifier	NOUN
ijassa-1442	119	22	that	that	PRON
ijassa-1442	119	23	is	be	AUX
ijassa-1442	119	24	both	both	CCONJ
ijassa-1442	119	25	fair	fair	ADJ
ijassa-1442	119	26	and	and	CCONJ
ijassa-1442	119	27	private	private	ADJ
ijassa-1442	119	28	.	.	PUNCT
ijassa-1442	120	1	the	the	DET
ijassa-1442	120	2	laftr	laftr	ADJ
ijassa-1442	120	3	model	model	NOUN
ijassa-1442	120	4	is	be	AUX
ijassa-1442	120	5	designed	design	VERB
ijassa-1442	120	6	to	to	PART
ijassa-1442	120	7	provide	provide	VERB
ijassa-1442	120	8	a	a	DET
ijassa-1442	120	9	fair	fair	ADJ
ijassa-1442	120	10	representation	representation	NOUN
ijassa-1442	120	11	.	.	PUNCT
ijassa-1442	121	1	differential	differential	PROPN
ijassa-1442	121	2	privacy	privacy	NOUN
ijassa-1442	121	3	,	,	PUNCT
ijassa-1442	121	4	which	which	PRON
ijassa-1442	121	5	adds	add	VERB
ijassa-1442	121	6	noise	noise	NOUN
ijassa-1442	121	7	to	to	ADP
ijassa-1442	121	8	the	the	DET
ijassa-1442	121	9	data	datum	NOUN
ijassa-1442	121	10	to	to	PART
ijassa-1442	121	11	protect	protect	VERB
ijassa-1442	121	12	individuals	individual	NOUN
ijassa-1442	121	13	'	'	PART
ijassa-1442	121	14	privacy	privacy	NOUN
ijassa-1442	121	15	,	,	PUNCT
ijassa-1442	121	16	is	be	AUX
ijassa-1442	121	17	utilized	utilize	VERB
ijassa-1442	121	18	as	as	ADP
ijassa-1442	121	19	the	the	DET
ijassa-1442	121	20	main	main	ADJ
ijassa-1442	121	21	method	method	NOUN
ijassa-1442	121	22	for	for	ADP
ijassa-1442	121	23	privacy	privacy	NOUN
ijassa-1442	121	24	preservation	preservation	NOUN
ijassa-1442	121	25	.	.	PUNCT
ijassa-1442	122	1	the	the	DET
ijassa-1442	122	2	integration	integration	NOUN
ijassa-1442	122	3	of	of	ADP
ijassa-1442	122	4	44	44	NUM
ijassa-1442	122	5	a.	a.	NOUN
ijassa-1442	122	6	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	122	7	,	,	PUNCT
ijassa-1442	122	8	r.	r.	PROPN
ijassa-1442	122	9	sabitov	sabitov	PROPN
ijassa-1442	122	10	,	,	PUNCT
ijassa-1442	122	11	g.	g.	PROPN
ijassa-1442	122	12	smirnova	smirnova	PROPN
ijassa-1442	122	13	,	,	PUNCT
ijassa-1442	122	14	sh	sh	PROPN
ijassa-1442	122	15	.	.	PUNCT
ijassa-1442	122	16	sabitov	sabitov	PROPN
ijassa-1442	122	17	copyright	copyright	NOUN
ijassa-1442	122	18	©	©	PROPN
ijassa-1442	122	19	2023	2023	NUM
ijassa-1442	122	20	assa	assa	PROPN
ijassa-1442	122	21	adv	adv	PROPN
ijassa-1442	122	22	.	.	PUNCT
ijassa-1442	123	1	in	in	ADP
ijassa-1442	123	2	systems	system	NOUN
ijassa-1442	123	3	science	science	NOUN
ijassa-1442	123	4	and	and	CCONJ
ijassa-1442	123	5	appl	appl	NOUN
ijassa-1442	123	6	.	.	PUNCT
ijassa-1442	124	1	(	(	PUNCT
ijassa-1442	124	2	2023	2023	NUM
ijassa-1442	124	3	)	)	PUNCT
ijassa-1442	124	4	algorithmic	algorithmic	ADJ
ijassa-1442	124	5	fairness	fairness	NOUN
ijassa-1442	124	6	and	and	CCONJ
ijassa-1442	124	7	differential	differential	NOUN
ijassa-1442	124	8	privacy	privacy	NOUN
ijassa-1442	124	9	is	be	AUX
ijassa-1442	124	10	a	a	DET
ijassa-1442	124	11	central	central	ADJ
ijassa-1442	124	12	focus	focus	NOUN
ijassa-1442	124	13	in	in	ADP
ijassa-1442	124	14	the	the	DET
ijassa-1442	124	15	training	training	NOUN
ijassa-1442	124	16	process	process	NOUN
ijassa-1442	124	17	of	of	ADP
ijassa-1442	124	18	the	the	DET
ijassa-1442	124	19	laftr	laftr	ADJ
ijassa-1442	124	20	model	model	NOUN
ijassa-1442	124	21	,	,	PUNCT
ijassa-1442	124	22	ensuring	ensure	VERB
ijassa-1442	124	23	that	that	SCONJ
ijassa-1442	124	24	the	the	DET
ijassa-1442	124	25	data	datum	NOUN
ijassa-1442	124	26	generated	generate	VERB
ijassa-1442	124	27	is	be	AUX
ijassa-1442	124	28	suitable	suitable	ADJ
ijassa-1442	124	29	for	for	ADP
ijassa-1442	124	30	use	use	NOUN
ijassa-1442	124	31	by	by	ADP
ijassa-1442	124	32	a	a	DET
ijassa-1442	124	33	third	third	ADJ
ijassa-1442	124	34	-	-	PUNCT
ijassa-1442	124	35	party	party	NOUN
ijassa-1442	124	36	classifier	classifier	NOUN
ijassa-1442	124	37	.	.	PUNCT
ijassa-1442	125	1	the	the	DET
ijassa-1442	125	2	paper	paper	NOUN
ijassa-1442	125	3	suggests	suggest	VERB
ijassa-1442	125	4	using	use	VERB
ijassa-1442	125	5	a	a	DET
ijassa-1442	125	6	third	third	ADJ
ijassa-1442	125	7	-	-	PUNCT
ijassa-1442	125	8	party	party	NOUN
ijassa-1442	125	9	classifier	classifier	NOUN
ijassa-1442	125	10	,	,	PUNCT
ijassa-1442	125	11	such	such	ADJ
ijassa-1442	125	12	as	as	ADP
ijassa-1442	125	13	logistic	logistic	ADJ
ijassa-1442	125	14	regression	regression	NOUN
ijassa-1442	125	15	,	,	PUNCT
ijassa-1442	125	16	to	to	PART
ijassa-1442	125	17	evaluate	evaluate	VERB
ijassa-1442	125	18	the	the	DET
ijassa-1442	125	19	fairness	fairness	NOUN
ijassa-1442	125	20	of	of	ADP
ijassa-1442	125	21	the	the	DET
ijassa-1442	125	22	data	datum	NOUN
ijassa-1442	125	23	generated	generate	VERB
ijassa-1442	125	24	by	by	ADP
ijassa-1442	125	25	the	the	DET
ijassa-1442	125	26	laftr	laftr	ADJ
ijassa-1442	125	27	model	model	NOUN
ijassa-1442	125	28	.	.	PUNCT
ijassa-1442	126	1	the	the	DET
ijassa-1442	126	2	logistic	logistic	ADJ
ijassa-1442	126	3	regression	regression	NOUN
ijassa-1442	126	4	model	model	NOUN
ijassa-1442	126	5	will	will	AUX
ijassa-1442	126	6	be	be	AUX
ijassa-1442	126	7	trained	train	VERB
ijassa-1442	126	8	on	on	ADP
ijassa-1442	126	9	the	the	DET
ijassa-1442	126	10	data	datum	NOUN
ijassa-1442	126	11	from	from	ADP
ijassa-1442	126	12	the	the	DET
ijassa-1442	126	13	latent	latent	NOUN
ijassa-1442	126	14	space	space	NOUN
ijassa-1442	126	15	,	,	PUNCT
ijassa-1442	126	16	which	which	PRON
ijassa-1442	126	17	has	have	AUX
ijassa-1442	126	18	undergone	undergo	VERB
ijassa-1442	126	19	in	in	ADP
ijassa-1442	126	20	-	-	PUNCT
ijassa-1442	126	21	processing	processing	NOUN
ijassa-1442	126	22	methods	method	NOUN
ijassa-1442	126	23	,	,	PUNCT
ijassa-1442	126	24	allowing	allow	VERB
ijassa-1442	126	25	us	we	PRON
ijassa-1442	126	26	to	to	PART
ijassa-1442	126	27	compare	compare	VERB
ijassa-1442	126	28	the	the	DET
ijassa-1442	126	29	performance	performance	NOUN
ijassa-1442	126	30	of	of	ADP
ijassa-1442	126	31	models	model	NOUN
ijassa-1442	126	32	trained	train	VERB
ijassa-1442	126	33	on	on	ADP
ijassa-1442	126	34	both	both	DET
ijassa-1442	126	35	raw	raw	ADJ
ijassa-1442	126	36	data	datum	NOUN
ijassa-1442	126	37	and	and	CCONJ
ijassa-1442	126	38	processed	process	VERB
ijassa-1442	126	39	data	datum	NOUN
ijassa-1442	126	40	.	.	PUNCT
ijassa-1442	127	1	mathematical	mathematical	ADJ
ijassa-1442	127	2	definition	definition	NOUN
ijassa-1442	127	3	of	of	ADP
ijassa-1442	127	4	the	the	DET
ijassa-1442	127	5	fairness	fairness	NOUN
ijassa-1442	127	6	variate	variate	NOUN
ijassa-1442	127	7	depends	depend	VERB
ijassa-1442	127	8	on	on	ADP
ijassa-1442	127	9	tasks	task	NOUN
ijassa-1442	127	10	.	.	PUNCT
ijassa-1442	128	1	in	in	ADP
ijassa-1442	128	2	this	this	DET
ijassa-1442	128	3	paper	paper	NOUN
ijassa-1442	128	4	we	we	PRON
ijassa-1442	128	5	will	will	AUX
ijassa-1442	128	6	use	use	VERB
ijassa-1442	128	7	two	two	NUM
ijassa-1442	128	8	popular	popular	ADJ
ijassa-1442	128	9	metrics	metric	NOUN
ijassa-1442	128	10	:	:	PUNCT
ijassa-1442	128	11	statistical	statistical	ADJ
ijassa-1442	128	12	(	(	PUNCT
ijassa-1442	128	13	demographic	demographic	ADJ
ijassa-1442	128	14	)	)	PUNCT
ijassa-1442	128	15	parity	parity	NOUN
ijassa-1442	128	16	and	and	CCONJ
ijassa-1442	128	17	equalized	equalize	VERB
ijassa-1442	128	18	odds	odd	NOUN
ijassa-1442	128	19	[	[	X
ijassa-1442	128	20	20	20	NUM
ijassa-1442	128	21	]	]	PUNCT
ijassa-1442	128	22	.	.	PUNCT
ijassa-1442	129	1	4	4	X
ijassa-1442	129	2	.	.	X
ijassa-1442	129	3	methodology	methodology	NOUN
ijassa-1442	129	4	in	in	ADP
ijassa-1442	129	5	this	this	DET
ijassa-1442	129	6	article	article	NOUN
ijassa-1442	129	7	,	,	PUNCT
ijassa-1442	129	8	we	we	PRON
ijassa-1442	129	9	investigate	investigate	VERB
ijassa-1442	129	10	the	the	DET
ijassa-1442	129	11	dependencies	dependency	NOUN
ijassa-1442	129	12	of	of	ADP
ijassa-1442	129	13	the	the	DET
ijassa-1442	129	14	impact	impact	NOUN
ijassa-1442	129	15	of	of	ADP
ijassa-1442	129	16	privacy	privacy	NOUN
ijassa-1442	129	17	injection	injection	NOUN
ijassa-1442	129	18	on	on	ADP
ijassa-1442	129	19	accuracy	accuracy	NOUN
ijassa-1442	129	20	and	and	CCONJ
ijassa-1442	129	21	fairness	fairness	NOUN
ijassa-1442	129	22	.	.	PUNCT
ijassa-1442	130	1	the	the	DET
ijassa-1442	130	2	laftr	laftr	ADJ
ijassa-1442	130	3	-	-	PUNCT
ijassa-1442	130	4	dp	dp	NOUN
ijassa-1442	130	5	and	and	CCONJ
ijassa-1442	130	6	laftr	laftr	NOUN
ijassa-1442	130	7	-	-	PUNCT
ijassa-1442	130	8	eod	eod	NOUN
ijassa-1442	130	9	[	[	X
ijassa-1442	130	10	17	17	NUM
ijassa-1442	130	11	]	]	PUNCT
ijassa-1442	130	12	models	model	NOUN
ijassa-1442	130	13	with	with	ADP
ijassa-1442	130	14	different	different	ADJ
ijassa-1442	130	15	privacy	privacy	NOUN
ijassa-1442	130	16	values	value	NOUN
ijassa-1442	130	17	in	in	ADP
ijassa-1442	130	18	different	different	ADJ
ijassa-1442	130	19	modules	module	NOUN
ijassa-1442	130	20	of	of	ADP
ijassa-1442	130	21	the	the	DET
ijassa-1442	130	22	model	model	NOUN
ijassa-1442	130	23	will	will	AUX
ijassa-1442	130	24	be	be	AUX
ijassa-1442	130	25	compared	compare	VERB
ijassa-1442	130	26	.	.	PUNCT
ijassa-1442	131	1	in	in	ADP
ijassa-1442	131	2	differential	differential	ADJ
ijassa-1442	131	3	privacy	privacy	NOUN
ijassa-1442	131	4	represents	represent	VERB
ijassa-1442	131	5	the	the	DET
ijassa-1442	131	6	privacy	privacy	NOUN
ijassa-1442	131	7	budget	budget	NOUN
ijassa-1442	131	8	that	that	PRON
ijassa-1442	131	9	determines	determine	VERB
ijassa-1442	131	10	the	the	DET
ijassa-1442	131	11	amount	amount	NOUN
ijassa-1442	131	12	of	of	ADP
ijassa-1442	131	13	noise	noise	NOUN
ijassa-1442	131	14	added	add	VERB
ijassa-1442	131	15	to	to	ADP
ijassa-1442	131	16	the	the	DET
ijassa-1442	131	17	gradients	gradient	NOUN
ijassa-1442	131	18	during	during	ADP
ijassa-1442	131	19	training	training	NOUN
ijassa-1442	131	20	,	,	PUNCT
ijassa-1442	131	21	where	where	SCONJ
ijassa-1442	131	22	a	a	DET
ijassa-1442	131	23	smaller	small	ADJ
ijassa-1442	131	24	corresponds	correspond	NOUN
ijassa-1442	131	25	to	to	ADP
ijassa-1442	131	26	stronger	strong	ADJ
ijassa-1442	131	27	privacy	privacy	NOUN
ijassa-1442	131	28	guarantees	guarantee	NOUN
ijassa-1442	131	29	but	but	CCONJ
ijassa-1442	131	30	potentially	potentially	ADV
ijassa-1442	131	31	higher	high	ADJ
ijassa-1442	131	32	noise	noise	NOUN
ijassa-1442	131	33	levels	level	NOUN
ijassa-1442	131	34	,	,	PUNCT
ijassa-1442	131	35	impacting	impact	VERB
ijassa-1442	131	36	the	the	DET
ijassa-1442	131	37	trade	trade	NOUN
ijassa-1442	131	38	-	-	PUNCT
ijassa-1442	131	39	off	off	NOUN
ijassa-1442	131	40	between	between	ADP
ijassa-1442	131	41	privacy	privacy	NOUN
ijassa-1442	131	42	and	and	CCONJ
ijassa-1442	131	43	utility	utility	NOUN
ijassa-1442	131	44	in	in	ADP
ijassa-1442	131	45	the	the	DET
ijassa-1442	131	46	learning	learning	NOUN
ijassa-1442	131	47	process	process	NOUN
ijassa-1442	131	48	.	.	PUNCT
ijassa-1442	132	1	these	these	DET
ijassa-1442	132	2	networks	network	NOUN
ijassa-1442	132	3	apply	apply	VERB
ijassa-1442	132	4	adversary	adversary	NOUN
ijassa-1442	132	5	training	training	NOUN
ijassa-1442	132	6	and	and	CCONJ
ijassa-1442	132	7	optimization	optimization	NOUN
ijassa-1442	132	8	using	use	VERB
ijassa-1442	132	9	dp	dp	NOUN
ijassa-1442	132	10	-	-	PUNCT
ijassa-1442	132	11	sgd	sgd	NOUN
ijassa-1442	132	12	to	to	PART
ijassa-1442	132	13	achieve	achieve	VERB
ijassa-1442	132	14	fairness	fairness	NOUN
ijassa-1442	132	15	and	and	CCONJ
ijassa-1442	132	16	guarantees	guarantee	NOUN
ijassa-1442	132	17	of	of	ADP
ijassa-1442	132	18	data	datum	NOUN
ijassa-1442	132	19	confidentiality	confidentiality	NOUN
ijassa-1442	132	20	.	.	PUNCT
ijassa-1442	133	1	4.1	4.1	NUM
ijassa-1442	133	2	.	.	PUNCT
ijassa-1442	133	3	dataset	dataset	NOUN
ijassa-1442	133	4	adult	adult	NOUN
ijassa-1442	133	5	dataset	dataset	NOUN
ijassa-1442	133	6	:	:	PUNCT
ijassa-1442	133	7	the	the	DET
ijassa-1442	133	8	adult	adult	NOUN
ijassa-1442	133	9	dataset	dataset	NOUN
ijassa-1442	133	10	is	be	AUX
ijassa-1442	133	11	a	a	DET
ijassa-1442	133	12	widely	widely	ADV
ijassa-1442	133	13	used	use	VERB
ijassa-1442	133	14	standard	standard	ADJ
ijassa-1442	133	15	machine	machine	NOUN
ijassa-1442	133	16	learning	learning	NOUN
ijassa-1442	133	17	dataset	dataset	VERB
ijassa-1442	133	18	for	for	ADP
ijassa-1442	133	19	studying	study	VERB
ijassa-1442	133	20	and	and	CCONJ
ijassa-1442	133	21	demonstrating	demonstrate	VERB
ijassa-1442	133	22	many	many	ADJ
ijassa-1442	133	23	common	common	ADJ
ijassa-1442	133	24	or	or	CCONJ
ijassa-1442	133	25	specially	specially	ADV
ijassa-1442	133	26	designed	design	VERB
ijassa-1442	133	27	machine	machine	NOUN
ijassa-1442	133	28	learning	learn	VERB
ijassa-1442	133	29	algorithms	algorithm	NOUN
ijassa-1442	133	30	for	for	ADP
ijassa-1442	133	31	unbalanced	unbalanced	ADJ
ijassa-1442	133	32	classification	classification	NOUN
ijassa-1442	133	33	.	.	PUNCT
ijassa-1442	134	1	in	in	ADP
ijassa-1442	134	2	total	total	NOUN
ijassa-1442	134	3	,	,	PUNCT
ijassa-1442	134	4	the	the	DET
ijassa-1442	134	5	data	datum	NOUN
ijassa-1442	134	6	set	set	VERB
ijassa-1442	134	7	(	(	PUNCT
ijassa-1442	134	8	train	train	NOUN
ijassa-1442	134	9	and	and	CCONJ
ijassa-1442	134	10	test	test	NOUN
ijassa-1442	134	11	)	)	PUNCT
ijassa-1442	134	12	contains	contain	VERB
ijassa-1442	134	13	48842	48842	NUM
ijassa-1442	134	14	samples	sample	NOUN
ijassa-1442	134	15	.	.	PUNCT
ijassa-1442	135	1	the	the	DET
ijassa-1442	135	2	dataset	dataset	NOUN
ijassa-1442	135	3	contains	contain	VERB
ijassa-1442	135	4	16	16	NUM
ijassa-1442	135	5	columns	column	NOUN
ijassa-1442	135	6	,	,	PUNCT
ijassa-1442	135	7	including	include	VERB
ijassa-1442	135	8	a	a	DET
ijassa-1442	135	9	target	target	NOUN
ijassa-1442	135	10	field	field	NOUN
ijassa-1442	135	11	“	"	PUNCT
ijassa-1442	135	12	income	income	NOUN
ijassa-1442	135	13	”	"	PUNCT
ijassa-1442	135	14	and	and	CCONJ
ijassa-1442	135	15	14	14	NUM
ijassa-1442	135	16	attributes	attribute	NOUN
ijassa-1442	135	17	that	that	PRON
ijassa-1442	135	18	describe	describe	VERB
ijassa-1442	135	19	a	a	DET
ijassa-1442	135	20	person	person	NOUN
ijassa-1442	135	21	's	's	PART
ijassa-1442	135	22	demographics	demographic	NOUN
ijassa-1442	135	23	and	and	CCONJ
ijassa-1442	135	24	other	other	ADJ
ijassa-1442	135	25	features	feature	NOUN
ijassa-1442	135	26	.	.	PUNCT
ijassa-1442	136	1	the	the	DET
ijassa-1442	136	2	income	income	NOUN
ijassa-1442	136	3	is	be	AUX
ijassa-1442	136	4	divided	divide	VERB
ijassa-1442	136	5	into	into	ADP
ijassa-1442	136	6	two	two	NUM
ijassa-1442	136	7	classes	class	NOUN
ijassa-1442	136	8	:	:	PUNCT
ijassa-1442	137	1	<	<	X
ijassa-1442	137	2	=	=	NOUN
ijassa-1442	137	3	50k	50k	NOUN
ijassa-1442	137	4	and	and	CCONJ
ijassa-1442	137	5	>	>	X
ijassa-1442	137	6	50k	50k	NUM
ijassa-1442	137	7	,	,	PUNCT
ijassa-1442	137	8	which	which	PRON
ijassa-1442	137	9	serves	serve	VERB
ijassa-1442	137	10	as	as	ADP
ijassa-1442	137	11	the	the	DET
ijassa-1442	137	12	target	target	NOUN
ijassa-1442	137	13	variable	variable	NOUN
ijassa-1442	137	14	for	for	ADP
ijassa-1442	137	15	the	the	DET
ijassa-1442	137	16	classification	classification	NOUN
ijassa-1442	137	17	task	task	NOUN
ijassa-1442	137	18	.	.	PUNCT
ijassa-1442	138	1	the	the	DET
ijassa-1442	138	2	dataset	dataset	NOUN
ijassa-1442	138	3	includes	include	VERB
ijassa-1442	138	4	various	various	ADJ
ijassa-1442	138	5	personal	personal	ADJ
ijassa-1442	138	6	information	information	NOUN
ijassa-1442	138	7	about	about	ADP
ijassa-1442	138	8	individuals	individual	NOUN
ijassa-1442	138	9	,	,	PUNCT
ijassa-1442	138	10	such	such	ADJ
ijassa-1442	138	11	as	as	ADP
ijassa-1442	138	12	their	their	PRON
ijassa-1442	138	13	age	age	NOUN
ijassa-1442	138	14	,	,	PUNCT
ijassa-1442	138	15	education	education	NOUN
ijassa-1442	138	16	level	level	NOUN
ijassa-1442	138	17	,	,	PUNCT
ijassa-1442	138	18	gender	gender	NOUN
ijassa-1442	138	19	,	,	PUNCT
ijassa-1442	138	20	occupation	occupation	NOUN
ijassa-1442	138	21	,	,	PUNCT
ijassa-1442	138	22	and	and	CCONJ
ijassa-1442	138	23	so	so	ADV
ijassa-1442	138	24	on	on	ADV
ijassa-1442	138	25	.	.	PUNCT
ijassa-1442	139	1	given	give	VERB
ijassa-1442	139	2	the	the	DET
ijassa-1442	139	3	characteristics	characteristic	NOUN
ijassa-1442	139	4	of	of	ADP
ijassa-1442	139	5	adult	adult	NOUN
ijassa-1442	139	6	recruitment	recruitment	NOUN
ijassa-1442	139	7	,	,	PUNCT
ijassa-1442	139	8	the	the	DET
ijassa-1442	139	9	classification	classification	NOUN
ijassa-1442	139	10	task	task	NOUN
ijassa-1442	139	11	is	be	AUX
ijassa-1442	139	12	to	to	PART
ijassa-1442	139	13	determine	determine	VERB
ijassa-1442	139	14	whether	whether	SCONJ
ijassa-1442	139	15	a	a	DET
ijassa-1442	139	16	person	person	NOUN
ijassa-1442	139	17	earns	earn	VERB
ijassa-1442	139	18	more	more	ADJ
ijassa-1442	139	19	than	than	ADP
ijassa-1442	139	20	50k	50k	NUM
ijassa-1442	139	21	or	or	CCONJ
ijassa-1442	139	22	less	less	ADJ
ijassa-1442	139	23	than	than	ADP
ijassa-1442	139	24	50k	50k	NUM
ijassa-1442	139	25	.	.	PUNCT
ijassa-1442	140	1	gender	gender	NOUN
ijassa-1442	140	2	was	be	AUX
ijassa-1442	140	3	selected	select	VERB
ijassa-1442	140	4	as	as	ADP
ijassa-1442	140	5	a	a	DET
ijassa-1442	140	6	protected	protect	VERB
ijassa-1442	140	7	attribute	attribute	NOUN
ijassa-1442	140	8	.	.	PUNCT
ijassa-1442	141	1	the	the	DET
ijassa-1442	141	2	size	size	NOUN
ijassa-1442	141	3	of	of	ADP
ijassa-1442	141	4	the	the	DET
ijassa-1442	141	5	test	test	NOUN
ijassa-1442	141	6	data	datum	NOUN
ijassa-1442	141	7	was	be	AUX
ijassa-1442	141	8	chosen	choose	VERB
ijassa-1442	141	9	to	to	PART
ijassa-1442	141	10	be	be	AUX
ijassa-1442	141	11	equal	equal	ADJ
ijassa-1442	141	12	to	to	ADP
ijassa-1442	141	13	30	30	NUM
ijassa-1442	141	14	%	%	NOUN
ijassa-1442	141	15	of	of	ADP
ijassa-1442	141	16	all	all	DET
ijassa-1442	141	17	data	datum	NOUN
ijassa-1442	141	18	.	.	PUNCT
ijassa-1442	142	1	4.2	4.2	NUM
ijassa-1442	142	2	.	.	PUNCT
ijassa-1442	142	3	model	model	VERB
ijassa-1442	142	4	the	the	DET
ijassa-1442	142	5	idea	idea	NOUN
ijassa-1442	142	6	is	be	AUX
ijassa-1442	142	7	to	to	PART
ijassa-1442	142	8	study	study	VERB
ijassa-1442	142	9	a	a	DET
ijassa-1442	142	10	representation	representation	NOUN
ijassa-1442	142	11	that	that	PRON
ijassa-1442	142	12	satisfies	satisfy	VERB
ijassa-1442	142	13	a	a	DET
ijassa-1442	142	14	certain	certain	ADJ
ijassa-1442	142	15	property	property	NOUN
ijassa-1442	142	16	of	of	ADP
ijassa-1442	142	17	fairness	fairness	NOUN
ijassa-1442	142	18	while	while	SCONJ
ijassa-1442	142	19	remaining	remain	VERB
ijassa-1442	142	20	differentially	differentially	ADV
ijassa-1442	142	21	private	private	ADJ
ijassa-1442	142	22	.	.	PUNCT
ijassa-1442	143	1	fig	fig	NOUN
ijassa-1442	143	2	.	.	PUNCT
ijassa-1442	144	1	1	1	NUM
ijassa-1442	144	2	shows	show	VERB
ijassa-1442	144	3	a	a	DET
ijassa-1442	144	4	network	network	NOUN
ijassa-1442	144	5	architecture	architecture	NOUN
ijassa-1442	144	6	that	that	PRON
ijassa-1442	144	7	seeks	seek	VERB
ijassa-1442	144	8	to	to	PART
ijassa-1442	144	9	study	study	VERB
ijassa-1442	144	10	a	a	DET
ijassa-1442	144	11	representation	representation	NOUN
ijassa-1442	144	12	of	of	ADP
ijassa-1442	144	13	data	datum	NOUN
ijassa-1442	144	14	capable	capable	ADJ
ijassa-1442	144	15	of	of	ADP
ijassa-1442	144	16	reconstructing	reconstruct	VERB
ijassa-1442	144	17	input	input	NOUN
ijassa-1442	144	18	data	datum	NOUN
ijassa-1442	144	19	,	,	PUNCT
ijassa-1442	144	20	classifying	classify	VERB
ijassa-1442	144	21	target	target	NOUN
ijassa-1442	144	22	labels	label	NOUN
ijassa-1442	144	23	,	,	PUNCT
ijassa-1442	144	24	and	and	CCONJ
ijassa-1442	144	25	protecting	protect	VERB
ijassa-1442	144	26	a	a	DET
ijassa-1442	144	27	sensitive	sensitive	ADJ
ijassa-1442	144	28	attribute	attribute	NOUN
ijassa-1442	144	29	(	(	PUNCT
ijassa-1442	144	30	fig	fig	NOUN
ijassa-1442	144	31	.	.	PUNCT
ijassa-1442	144	32	1	1	NUM
ijassa-1442	144	33	)	)	PUNCT
ijassa-1442	144	34	.	.	PUNCT
ijassa-1442	145	1	the	the	DET
ijassa-1442	145	2	loss	loss	NOUN
ijassa-1442	145	3	function	function	NOUN
ijassa-1442	145	4	of	of	ADP
ijassa-1442	145	5	the	the	DET
ijassa-1442	145	6	network	network	NOUN
ijassa-1442	145	7	is	be	AUX
ijassa-1442	145	8	defined	define	VERB
ijassa-1442	145	9	as	as	ADP
ijassa-1442	145	10	a	a	DET
ijassa-1442	145	11	linear	linear	ADJ
ijassa-1442	145	12	combination	combination	NOUN
ijassa-1442	145	13	of	of	ADP
ijassa-1442	145	14	three	three	NUM
ijassa-1442	145	15	loss	loss	NOUN
ijassa-1442	145	16	terms	term	NOUN
ijassa-1442	145	17	,	,	PUNCT
ijassa-1442	145	18	the	the	DET
ijassa-1442	145	19	reconstruction	reconstruction	NOUN
ijassa-1442	145	20	loss	loss	NOUN
ijassa-1442	145	21	,	,	PUNCT
ijassa-1442	145	22	the	the	DET
ijassa-1442	145	23	adversary	adversary	NOUN
ijassa-1442	145	24	loss	loss	NOUN
ijassa-1442	145	25	,	,	PUNCT
ijassa-1442	145	26	and	and	CCONJ
ijassa-1442	145	27	prediction	prediction	NOUN
ijassa-1442	145	28	loss	loss	NOUN
ijassa-1442	146	1	[	[	X
ijassa-1442	146	2	9	9	NUM
ijassa-1442	146	3	]	]	SYM
ijassa-1442	146	4	:	:	PUNCT
ijassa-1442	146	5	where	where	SCONJ
ijassa-1442	146	6	,	,	PUNCT
ijassa-1442	146	7	and	and	CCONJ
ijassa-1442	146	8	are	be	AUX
ijassa-1442	146	9	hyperparameters	hyperparameter	NOUN
ijassa-1442	146	10	controlling	control	VERB
ijassa-1442	146	11	the	the	DET
ijassa-1442	146	12	weighting	weighting	NOUN
ijassa-1442	146	13	of	of	ADP
ijassa-1442	146	14	the	the	DET
ijassa-1442	146	15	competing	compete	VERB
ijassa-1442	146	16	objectives	objective	NOUN
ijassa-1442	146	17	.	.	PUNCT
ijassa-1442	147	1	the	the	DET
ijassa-1442	147	2	decoder	decoder	NOUN
ijassa-1442	147	3	reconstructs	reconstruct	VERB
ijassa-1442	147	4	input	input	NOUN
ijassa-1442	147	5	data	datum	NOUN
ijassa-1442	147	6	from	from	ADP
ijassa-1442	147	7	the	the	DET
ijassa-1442	147	8	latent	latent	NOUN
ijassa-1442	147	9	space	space	NOUN
ijassa-1442	147	10	.	.	PUNCT
ijassa-1442	148	1	the	the	DET
ijassa-1442	148	2	classifier	classifier	NOUN
ijassa-1442	148	3	predicts	predict	VERB
ijassa-1442	148	4	the	the	DET
ijassa-1442	148	5	class	class	NOUN
ijassa-1442	148	6	label	label	NOUN
ijassa-1442	148	7	from	from	ADP
ijassa-1442	148	8	latent	latent	ADJ
ijassa-1442	148	9	space	space	NOUN
ijassa-1442	148	10	.	.	PUNCT
ijassa-1442	149	1	the	the	DET
ijassa-1442	149	2	adversarial	adversarial	ADJ
ijassa-1442	149	3	loss	loss	NOUN
ijassa-1442	149	4	is	be	AUX
ijassa-1442	149	5	to	to	PART
ijassa-1442	149	6	enforce	enforce	VERB
ijassa-1442	149	7	the	the	DET
ijassa-1442	149	8	representation	representation	NOUN
ijassa-1442	149	9	(	(	PUNCT
ijassa-1442	149	10	latent	latent	NOUN
ijassa-1442	149	11	space	space	NOUN
ijassa-1442	149	12	)	)	PUNCT
ijassa-1442	149	13	to	to	PART
ijassa-1442	149	14	satisfy	satisfy	VERB
ijassa-1442	149	15	a	a	DET
ijassa-1442	149	16	certain	certain	ADJ
ijassa-1442	149	17	fairness	fairness	NOUN
ijassa-1442	149	18	notion	notion	NOUN
ijassa-1442	149	19	.	.	PUNCT
ijassa-1442	150	1	any	any	PRON
ijassa-1442	150	2	of	of	ADP
ijassa-1442	150	3	the	the	DET
ijassa-1442	150	4	first	first	ADJ
ijassa-1442	150	5	two	two	NUM
ijassa-1442	150	6	requirements	requirement	NOUN
ijassa-1442	150	7	can	can	AUX
ijassa-1442	150	8	be	be	AUX
ijassa-1442	150	9	omitted	omit	VERB
ijassa-1442	150	10	by	by	ADP
ijassa-1442	150	11	setting	set	VERB
ijassa-1442	150	12	the	the	DET
ijassa-1442	150	13	hyperparameters	hyperparameter	NOUN
ijassa-1442	150	14	to	to	ADP
ijassa-1442	150	15	zero	zero	NUM
ijassa-1442	150	16	.	.	PUNCT
ijassa-1442	151	1	to	to	PART
ijassa-1442	151	2	improve	improve	VERB
ijassa-1442	151	3	fair	fair	ADJ
ijassa-1442	151	4	metrics	metric	NOUN
ijassa-1442	151	5	,	,	PUNCT
ijassa-1442	151	6	which	which	PRON
ijassa-1442	151	7	defined	define	VERB
ijassa-1442	151	8	in	in	ADP
ijassa-1442	151	9	background	background	NOUN
ijassa-1442	151	10	section	section	NOUN
ijassa-1442	151	11	,	,	PUNCT
ijassa-1442	151	12	loss	loss	NOUN
ijassa-1442	151	13	functions	function	NOUN
ijassa-1442	151	14	can	can	AUX
ijassa-1442	151	15	be	be	AUX
ijassa-1442	151	16	defined	define	VERB
ijassa-1442	151	17	as	as	ADP
ijassa-1442	151	18	[	[	X
ijassa-1442	151	19	9	9	NUM
ijassa-1442	151	20	]	]	NUM
ijassa-1442	151	21	:	:	PUNCT
ijassa-1442	151	22	,	,	PUNCT
ijassa-1442	151	23	,	,	PUNCT
ijassa-1442	151	24	balancing	balance	VERB
ijassa-1442	151	25	accuracy	accuracy	NOUN
ijassa-1442	151	26	,	,	PUNCT
ijassa-1442	151	27	fairness	fairness	NOUN
ijassa-1442	151	28	and	and	CCONJ
ijassa-1442	151	29	privacy	privacy	NOUN
ijassa-1442	151	30	in	in	ADP
ijassa-1442	151	31	machine	machine	NOUN
ijassa-1442	151	32	learning	learning	NOUN
ijassa-1442	151	33	…	…	PUNCT
ijassa-1442	151	34	45	45	NUM
ijassa-1442	151	35	copyright	copyright	NOUN
ijassa-1442	151	36	©	©	PROPN
ijassa-1442	151	37	2023	2023	NUM
ijassa-1442	151	38	assa	assa	NOUN
ijassa-1442	151	39	.	.	PUNCT
ijassa-1442	152	1	adv	adv	PROPN
ijassa-1442	152	2	.	.	PUNCT
ijassa-1442	153	1	in	in	ADP
ijassa-1442	153	2	systems	system	NOUN
ijassa-1442	153	3	science	science	NOUN
ijassa-1442	153	4	and	and	CCONJ
ijassa-1442	153	5	appl	appl	NOUN
ijassa-1442	153	6	.	.	PUNCT
ijassa-1442	154	1	(	(	PUNCT
ijassa-1442	154	2	2023	2023	NUM
ijassa-1442	154	3	)	)	PUNCT
ijassa-1442	154	4	,	,	PUNCT
ijassa-1442	154	5	where	where	SCONJ
ijassa-1442	154	6	adversary	adversary	NOUN
ijassa-1442	154	7	,	,	PUNCT
ijassa-1442	154	8	classifier	classifier	NOUN
ijassa-1442	154	9	,	,	PUNCT
ijassa-1442	154	10	encoder	encoder	NOUN
ijassa-1442	154	11	,	,	PUNCT
ijassa-1442	154	12	decoder	decoder	NOUN
ijassa-1442	154	13	.	.	PUNCT
ijassa-1442	155	1	also	also	ADV
ijassa-1442	155	2	,	,	PUNCT
ijassa-1442	155	3	the	the	DET
ijassa-1442	155	4	objective	objective	NOUN
ijassa-1442	155	5	of	of	ADP
ijassa-1442	155	6	the	the	DET
ijassa-1442	155	7	network	network	NOUN
ijassa-1442	155	8	is	be	AUX
ijassa-1442	155	9	not	not	PART
ijassa-1442	155	10	only	only	ADV
ijassa-1442	155	11	to	to	PART
ijassa-1442	155	12	make	make	VERB
ijassa-1442	155	13	the	the	DET
ijassa-1442	155	14	representation	representation	NOUN
ijassa-1442	155	15	fair	fair	ADJ
ijassa-1442	155	16	,	,	PUNCT
ijassa-1442	155	17	but	but	CCONJ
ijassa-1442	155	18	also	also	ADV
ijassa-1442	155	19	to	to	PART
ijassa-1442	155	20	be	be	AUX
ijassa-1442	155	21	privacy	privacy	NOUN
ijassa-1442	155	22	preserving	preserve	VERB
ijassa-1442	155	23	.	.	PUNCT
ijassa-1442	156	1	in	in	ADP
ijassa-1442	156	2	this	this	DET
ijassa-1442	156	3	regard	regard	NOUN
ijassa-1442	156	4	,	,	PUNCT
ijassa-1442	156	5	we	we	PRON
ijassa-1442	156	6	propose	propose	VERB
ijassa-1442	156	7	to	to	PART
ijassa-1442	156	8	train	train	VERB
ijassa-1442	156	9	the	the	DET
ijassa-1442	156	10	network	network	NOUN
ijassa-1442	156	11	with	with	ADP
ijassa-1442	156	12	privacy	privacy	NOUN
ijassa-1442	156	13	preserving	preserve	VERB
ijassa-1442	156	14	techniques	technique	NOUN
ijassa-1442	156	15	such	such	ADJ
ijassa-1442	156	16	as	as	ADP
ijassa-1442	156	17	dp	dp	NOUN
ijassa-1442	156	18	-	-	PUNCT
ijassa-1442	156	19	sgd	sgd	NOUN
ijassa-1442	156	20	.	.	PUNCT
ijassa-1442	156	21	fig	fig	NOUN
ijassa-1442	156	22	.	.	PUNCT
ijassa-1442	157	1	1	1	NUM
ijassa-1442	157	2	.	.	X
ijassa-1442	157	3	laftr	laftr	ADJ
ijassa-1442	157	4	model	model	NOUN
ijassa-1442	157	5	with	with	ADP
ijassa-1442	157	6	dp	dp	NOUN
ijassa-1442	157	7	-	-	ADJ
ijassa-1442	157	8	sgd	sgd	NOUN
ijassa-1442	157	9	in	in	ADP
ijassa-1442	157	10	(	(	PUNCT
ijassa-1442	157	11	a	a	X
ijassa-1442	157	12	)	)	PUNCT
ijassa-1442	157	13	encoder/	encoder/	NUM
ijassa-1442	157	14	classifier	classifier	NOUN
ijassa-1442	157	15	,	,	PUNCT
ijassa-1442	157	16	(	(	PUNCT
ijassa-1442	157	17	b	b	NOUN
ijassa-1442	157	18	)	)	PUNCT
ijassa-1442	157	19	encoder	encoder	NOUN
ijassa-1442	157	20	/	/	SYM
ijassa-1442	157	21	classifier	classifier	NOUN
ijassa-1442	157	22	/	/	SYM
ijassa-1442	157	23	adversary	adversary	NOUN
ijassa-1442	157	24	to	to	PART
ijassa-1442	157	25	make	make	VERB
ijassa-1442	157	26	latent	latent	ADJ
ijassa-1442	157	27	space	space	NOUN
ijassa-1442	157	28	confidential	confidential	ADJ
ijassa-1442	157	29	we	we	PRON
ijassa-1442	157	30	need	need	VERB
ijassa-1442	157	31	to	to	PART
ijassa-1442	157	32	introduce	introduce	VERB
ijassa-1442	157	33	dp	dp	ADJ
ijassa-1442	157	34	-	-	PUNCT
ijassa-1442	157	35	sgd	sgd	ADJ
ijassa-1442	157	36	method	method	NOUN
ijassa-1442	157	37	in	in	ADP
ijassa-1442	157	38	encoder	encoder	NOUN
ijassa-1442	157	39	.	.	PUNCT
ijassa-1442	158	1	also	also	ADV
ijassa-1442	158	2	,	,	PUNCT
ijassa-1442	158	3	in	in	ADP
ijassa-1442	158	4	this	this	DET
ijassa-1442	158	5	work	work	NOUN
ijassa-1442	158	6	we	we	PRON
ijassa-1442	158	7	will	will	AUX
ijassa-1442	158	8	inject	inject	VERB
ijassa-1442	158	9	privacy	privacy	NOUN
ijassa-1442	158	10	in	in	ADP
ijassa-1442	158	11	classifier	classifier	NOUN
ijassa-1442	158	12	and	and	CCONJ
ijassa-1442	158	13	adversary	adversary	NOUN
ijassa-1442	158	14	modules	module	NOUN
ijassa-1442	158	15	(	(	PUNCT
ijassa-1442	158	16	fig	fig	NOUN
ijassa-1442	158	17	.	.	PUNCT
ijassa-1442	158	18	1	1	NUM
ijassa-1442	158	19	)	)	PUNCT
ijassa-1442	158	20	.	.	PUNCT
ijassa-1442	159	1	in	in	ADP
ijassa-1442	159	2	addition	addition	NOUN
ijassa-1442	159	3	,	,	PUNCT
ijassa-1442	159	4	in	in	ADP
ijassa-1442	159	5	this	this	DET
ijassa-1442	159	6	work	work	NOUN
ijassa-1442	159	7	,	,	PUNCT
ijassa-1442	159	8	two	two	NUM
ijassa-1442	159	9	types	type	NOUN
ijassa-1442	159	10	of	of	ADP
ijassa-1442	159	11	laftr	laftr	ADJ
ijassa-1442	159	12	models	model	NOUN
ijassa-1442	159	13	(	(	PUNCT
ijassa-1442	159	14	laftr	laftr	NOUN
ijassa-1442	159	15	-	-	PUNCT
ijassa-1442	159	16	dp	dp	NOUN
ijassa-1442	159	17	and	and	CCONJ
ijassa-1442	159	18	laftr	laftr	ADJ
ijassa-1442	159	19	-	-	PUNCT
ijassa-1442	159	20	eod	eod	NOUN
ijassa-1442	159	21	)	)	PUNCT
ijassa-1442	159	22	are	be	AUX
ijassa-1442	159	23	considered	consider	VERB
ijassa-1442	159	24	.	.	PUNCT
ijassa-1442	160	1	the	the	DET
ijassa-1442	160	2	only	only	ADJ
ijassa-1442	160	3	difference	difference	NOUN
ijassa-1442	160	4	between	between	ADP
ijassa-1442	160	5	laftr	laftr	NOUN
ijassa-1442	160	6	-	-	PUNCT
ijassa-1442	160	7	dp	dp	NOUN
ijassa-1442	160	8	and	and	CCONJ
ijassa-1442	160	9	laftr	laftr	ADJ
ijassa-1442	160	10	-	-	PUNCT
ijassa-1442	160	11	eod	eod	NOUN
ijassa-1442	160	12	models	model	NOUN
ijassa-1442	160	13	is	be	AUX
ijassa-1442	160	14	that	that	SCONJ
ijassa-1442	160	15	in	in	ADP
ijassa-1442	160	16	laftr	laftr	ADJ
ijassa-1442	160	17	-	-	PUNCT
ijassa-1442	160	18	eod	eod	NOUN
ijassa-1442	160	19	approach	approach	NOUN
ijassa-1442	160	20	we	we	PRON
ijassa-1442	160	21	pass	pass	VERB
ijassa-1442	160	22	to	to	ADP
ijassa-1442	160	23	adversary	adversary	NOUN
ijassa-1442	160	24	not	not	PART
ijassa-1442	160	25	only	only	ADV
ijassa-1442	160	26	,	,	PUNCT
ijassa-1442	160	27	but	but	CCONJ
ijassa-1442	160	28	we	we	PRON
ijassa-1442	160	29	pass	pass	VERB
ijassa-1442	160	30	class	class	NOUN
ijassa-1442	160	31	label	label	NOUN
ijassa-1442	160	32	in	in	ADP
ijassa-1442	160	33	addition	addition	NOUN
ijassa-1442	160	34	.	.	PUNCT
ijassa-1442	161	1	4.3	4.3	NUM
ijassa-1442	161	2	.	.	PUNCT
ijassa-1442	161	3	training	training	NOUN
ijassa-1442	161	4	laftr	laftr	NOUN
ijassa-1442	161	5	seeks	seek	VERB
ijassa-1442	161	6	to	to	PART
ijassa-1442	161	7	study	study	VERB
ijassa-1442	161	8	the	the	DET
ijassa-1442	161	9	encoder	encoder	NOUN
ijassa-1442	161	10	that	that	PRON
ijassa-1442	161	11	gives	give	VERB
ijassa-1442	161	12	reliable	reliable	ADJ
ijassa-1442	161	13	representations	representation	NOUN
ijassa-1442	161	14	,	,	PUNCT
ijassa-1442	161	15	i.e.	i.e.	X
ijassa-1442	161	16	the	the	DET
ijassa-1442	161	17	output	output	NOUN
ijassa-1442	161	18	of	of	ADP
ijassa-1442	161	19	the	the	DET
ijassa-1442	161	20	encoder	encoder	NOUN
ijassa-1442	161	21	can	can	AUX
ijassa-1442	161	22	be	be	AUX
ijassa-1442	161	23	used	use	VERB
ijassa-1442	161	24	by	by	ADP
ijassa-1442	161	25	third	third	ADJ
ijassa-1442	161	26	parties	party	NOUN
ijassa-1442	161	27	with	with	ADP
ijassa-1442	161	28	confidence	confidence	NOUN
ijassa-1442	161	29	that	that	SCONJ
ijassa-1442	161	30	their	their	PRON
ijassa-1442	161	31	naively	naively	ADV
ijassa-1442	161	32	trained	train	VERB
ijassa-1442	161	33	classifiers	classifier	NOUN
ijassa-1442	161	34	be	be	AUX
ijassa-1442	161	35	fairly	fairly	ADV
ijassa-1442	161	36	fair	fair	ADJ
ijassa-1442	161	37	,	,	PUNCT
ijassa-1442	161	38	private	private	ADJ
ijassa-1442	161	39	and	and	CCONJ
ijassa-1442	161	40	accurate	accurate	ADJ
ijassa-1442	161	41	.	.	PUNCT
ijassa-1442	162	1	algorithm	algorithm	PROPN
ijassa-1442	162	2	below	below	ADV
ijassa-1442	162	3	describes	describe	VERB
ijassa-1442	162	4	the	the	DET
ijassa-1442	162	5	training	training	NOUN
ijassa-1442	162	6	process	process	NOUN
ijassa-1442	162	7	of	of	ADP
ijassa-1442	162	8	laftr	laftr	NOUN
ijassa-1442	162	9	with	with	ADP
ijassa-1442	162	10	privacy	privacy	NOUN
ijassa-1442	162	11	preservation	preservation	NOUN
ijassa-1442	162	12	.	.	PUNCT
ijassa-1442	163	1	the	the	DET
ijassa-1442	163	2	detailed	detailed	ADJ
ijassa-1442	163	3	pseudocode	pseudocode	NOUN
ijassa-1442	163	4	is	be	AUX
ijassa-1442	163	5	described	describe	VERB
ijassa-1442	163	6	in	in	ADP
ijassa-1442	163	7	algorithm	algorithm	NOUN
ijassa-1442	163	8	1	1	NUM
ijassa-1442	163	9	.	.	PUNCT
ijassa-1442	163	10	algorithm	algorithm	NOUN
ijassa-1442	163	11	1	1	NUM
ijassa-1442	163	12	:	:	PUNCT
ijassa-1442	163	13	differentially	differentially	ADV
ijassa-1442	163	14	private	private	ADJ
ijassa-1442	163	15	sgd	sgd	NOUN
ijassa-1442	163	16	on	on	ADP
ijassa-1442	163	17	learning	learn	VERB
ijassa-1442	163	18	under	under	ADP
ijassa-1442	163	19	adversary	adversary	ADJ
ijassa-1442	163	20	input	input	NOUN
ijassa-1442	163	21	:	:	PUNCT
ijassa-1442	163	22	dataset	dataset	NOUN
ijassa-1442	163	23	;	;	PUNCT
ijassa-1442	163	24	batch	batch	NOUN
ijassa-1442	163	25	size	size	NOUN
ijassa-1442	163	26	;	;	PUNCT
ijassa-1442	164	1	learning	learn	VERB
ijassa-1442	164	2	rate	rate	NOUN
ijassa-1442	164	3	;	;	PUNCT
ijassa-1442	164	4	iterations	iteration	NOUN
ijassa-1442	164	5	;	;	PUNCT
ijassa-1442	164	6	noise	noise	NOUN
ijassa-1442	164	7	;	;	PUNCT
ijassa-1442	164	8	clipping	clip	VERB
ijassa-1442	164	9	bound	bind	VERB
ijassa-1442	164	10	;	;	PUNCT
ijassa-1442	164	11	hyperparameters	hyperparameter	NOUN
ijassa-1442	164	12	controlling	control	VERB
ijassa-1442	164	13	the	the	DET
ijassa-1442	164	14	weighting	weighting	NOUN
ijassa-1442	164	15	(	(	PUNCT
ijassa-1442	164	16	,	,	PUNCT
ijassa-1442	164	17	and	and	CCONJ
ijassa-1442	164	18	)	)	PUNCT
ijassa-1442	164	19	;	;	PUNCT
ijassa-1442	164	20	component	component	NOUN
ijassa-1442	164	21	for	for	ADP
ijassa-1442	164	22	privacy	privacy	NOUN
ijassa-1442	164	23	preservation	preservation	NOUN
ijassa-1442	164	24	(	(	PUNCT
ijassa-1442	164	25	(	(	PUNCT
ijassa-1442	164	26	for	for	ADP
ijassa-1442	164	27	and	and	CCONJ
ijassa-1442	164	28	)	)	PUNCT
ijassa-1442	164	29	or	or	CCONJ
ijassa-1442	164	30	(	(	PUNCT
ijassa-1442	164	31	for	for	ADP
ijassa-1442	164	32	)	)	PUNCT
ijassa-1442	164	33	or	or	CCONJ
ijassa-1442	164	34	(	(	PUNCT
ijassa-1442	164	35	for	for	ADP
ijassa-1442	164	36	)	)	PUNCT
ijassa-1442	164	37	)	)	PUNCT
ijassa-1442	164	38	as	as	ADP
ijassa-1442	164	39	;	;	PUNCT
ijassa-1442	164	40	loss	loss	NOUN
ijassa-1442	164	41	function	function	NOUN
ijassa-1442	164	42	initialize	initialize	NOUN
ijassa-1442	164	43	network	network	NOUN
ijassa-1442	164	44	parameters	parameter	NOUN
ijassa-1442	164	45	(	(	PUNCT
ijassa-1442	164	46	encoder	encoder	NOUN
ijassa-1442	164	47	,	,	PUNCT
ijassa-1442	164	48	classifier	classifier	NOUN
ijassa-1442	164	49	,	,	PUNCT
ijassa-1442	164	50	adversary	adversary	NOUN
ijassa-1442	164	51	respectively	respectively	ADV
ijassa-1442	164	52	)	)	PUNCT
ijassa-1442	164	53	true	true	ADJ
ijassa-1442	164	54	(	(	PUNCT
ijassa-1442	164	55	boolean	boolean	ADJ
ijassa-1442	164	56	indicating	indicate	VERB
ijassa-1442	164	57	whether	whether	SCONJ
ijassa-1442	164	58	to	to	PART
ijassa-1442	164	59	update	update	VERB
ijassa-1442	164	60	parameters	parameter	NOUN
ijassa-1442	164	61	)	)	PUNCT
ijassa-1442	164	62	for	for	ADP
ijassa-1442	164	63	k	k	PROPN
ijassa-1442	164	64	do	do	AUX
ijassa-1442	164	65	if	if	SCONJ
ijassa-1442	164	66	then	then	ADV
ijassa-1442	164	67	select	select	VERB
ijassa-1442	164	68	next	next	ADJ
ijassa-1442	164	69	batch	batch	NOUN
ijassa-1442	164	70	;	;	PUNCT
ijassa-1442	164	71	foreach	foreach	NOUN
ijassa-1442	164	72	in	in	ADP
ijassa-1442	164	73	batch	batch	NOUN
ijassa-1442	164	74	do	do	VERB
ijassa-1442	164	75	compute	compute	NOUN
ijassa-1442	164	76	gradients	gradient	NOUN
ijassa-1442	164	77	for	for	ADP
ijassa-1442	164	78	each	each	DET
ijassa-1442	164	79	module	module	NOUN
ijassa-1442	164	80	:	:	PUNCT
ijassa-1442	164	81	clip	clip	NOUN
ijassa-1442	164	82	gradients	gradient	NOUN
ijassa-1442	164	83	:	:	PUNCT
ijassa-1442	164	84	46	46	NUM
ijassa-1442	164	85	a.	a.	NOUN
ijassa-1442	164	86	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	164	87	,	,	PUNCT
ijassa-1442	164	88	r.	r.	PROPN
ijassa-1442	164	89	sabitov	sabitov	PROPN
ijassa-1442	164	90	,	,	PUNCT
ijassa-1442	164	91	g.	g.	PROPN
ijassa-1442	164	92	smirnova	smirnova	PROPN
ijassa-1442	164	93	,	,	PUNCT
ijassa-1442	164	94	sh	sh	PROPN
ijassa-1442	164	95	.	.	PUNCT
ijassa-1442	164	96	sabitov	sabitov	PROPN
ijassa-1442	164	97	copyright	copyright	NOUN
ijassa-1442	164	98	©	©	PROPN
ijassa-1442	164	99	2023	2023	NUM
ijassa-1442	164	100	assa	assa	PROPN
ijassa-1442	164	101	adv	adv	PROPN
ijassa-1442	164	102	.	.	PUNCT
ijassa-1442	165	1	in	in	ADP
ijassa-1442	165	2	systems	system	NOUN
ijassa-1442	165	3	science	science	NOUN
ijassa-1442	165	4	and	and	CCONJ
ijassa-1442	165	5	appl	appl	NOUN
ijassa-1442	165	6	.	.	PUNCT
ijassa-1442	166	1	(	(	PUNCT
ijassa-1442	166	2	2023	2023	NUM
ijassa-1442	166	3	)	)	PUNCT
ijassa-1442	166	4	end	end	NOUN
ijassa-1442	166	5	add	add	VERB
ijassa-1442	166	6	noise	noise	NOUN
ijassa-1442	166	7	to	to	ADP
ijassa-1442	166	8	selected	select	VERB
ijassa-1442	166	9	component	component	NOUN
ijassa-1442	166	10	:	:	PUNCT
ijassa-1442	166	11	sum	sum	VERB
ijassa-1442	166	12	other	other	ADJ
ijassa-1442	166	13	gradients	gradient	NOUN
ijassa-1442	166	14	:	:	PUNCT
ijassa-1442	166	15	descent	descent	NOUN
ijassa-1442	166	16	:	:	PUNCT
ijassa-1442	166	17	if	if	SCONJ
ijassa-1442	166	18	then	then	ADV
ijassa-1442	166	19	else	else	ADV
ijassa-1442	166	20	end	end	VERB
ijassa-1442	166	21	end	end	NOUN
ijassa-1442	166	22	in	in	ADP
ijassa-1442	166	23	short	short	ADJ
ijassa-1442	166	24	,	,	PUNCT
ijassa-1442	166	25	it	it	PRON
ijassa-1442	166	26	is	be	AUX
ijassa-1442	166	27	a	a	DET
ijassa-1442	166	28	combination	combination	NOUN
ijassa-1442	166	29	of	of	ADP
ijassa-1442	166	30	adversarial	adversarial	ADJ
ijassa-1442	166	31	learned	learn	VERB
ijassa-1442	166	32	fair	fair	ADJ
ijassa-1442	166	33	representations	representation	NOUN
ijassa-1442	166	34	[	[	X
ijassa-1442	166	35	9	9	NUM
ijassa-1442	166	36	]	]	PUNCT
ijassa-1442	166	37	and	and	CCONJ
ijassa-1442	166	38	dp	dp	ADJ
ijassa-1442	166	39	-	-	ADJ
ijassa-1442	166	40	sgd	sgd	NOUN
ijassa-1442	166	41	[	[	X
ijassa-1442	166	42	1	1	NUM
ijassa-1442	166	43	]	]	PUNCT
ijassa-1442	166	44	.	.	PUNCT
ijassa-1442	167	1	we	we	PRON
ijassa-1442	167	2	learn	learn	VERB
ijassa-1442	167	3	encoder	encoder	NOUN
ijassa-1442	167	4	and	and	CCONJ
ijassa-1442	167	5	classifier	classifier	VERB
ijassa-1442	167	6	with	with	ADP
ijassa-1442	167	7	gradient	gradient	NOUN
ijassa-1442	167	8	clipping	clip	VERB
ijassa-1442	167	9	and	and	CCONJ
ijassa-1442	167	10	adding	add	VERB
ijassa-1442	167	11	noise	noise	NOUN
ijassa-1442	167	12	if	if	SCONJ
ijassa-1442	167	13	necessary	necessary	ADJ
ijassa-1442	167	14	.	.	PUNCT
ijassa-1442	168	1	then	then	ADV
ijassa-1442	168	2	we	we	PRON
ijassa-1442	168	3	freeze	freeze	VERB
ijassa-1442	168	4	the	the	DET
ijassa-1442	168	5	learned	learn	VERB
ijassa-1442	168	6	encoder	encoder	NOUN
ijassa-1442	168	7	and	and	CCONJ
ijassa-1442	168	8	classifier	classifier	VERB
ijassa-1442	168	9	and	and	CCONJ
ijassa-1442	168	10	learn	learn	VERB
ijassa-1442	168	11	the	the	DET
ijassa-1442	168	12	adversary	adversary	NOUN
ijassa-1442	168	13	part	part	NOUN
ijassa-1442	168	14	with	with	ADP
ijassa-1442	168	15	gradient	gradient	NOUN
ijassa-1442	168	16	clipping	clip	VERB
ijassa-1442	168	17	and	and	CCONJ
ijassa-1442	168	18	adding	add	VERB
ijassa-1442	168	19	noise	noise	NOUN
ijassa-1442	168	20	if	if	SCONJ
ijassa-1442	168	21	necessary	necessary	ADJ
ijassa-1442	168	22	.	.	PUNCT
ijassa-1442	169	1	the	the	DET
ijassa-1442	169	2	overall	overall	ADJ
ijassa-1442	169	3	loss	loss	NOUN
ijassa-1442	169	4	function	function	NOUN
ijassa-1442	169	5	is	be	AUX
ijassa-1442	169	6	a	a	DET
ijassa-1442	169	7	combination	combination	NOUN
ijassa-1442	169	8	of	of	ADP
ijassa-1442	169	9	these	these	DET
ijassa-1442	169	10	loss	loss	NOUN
ijassa-1442	169	11	functions	function	NOUN
ijassa-1442	169	12	with	with	ADP
ijassa-1442	169	13	hyperparameters	hyperparameter	NOUN
ijassa-1442	169	14	controlling	control	VERB
ijassa-1442	169	15	the	the	DET
ijassa-1442	169	16	weighting	weighting	NOUN
ijassa-1442	169	17	.	.	PUNCT
ijassa-1442	170	1	the	the	DET
ijassa-1442	170	2	training	training	NOUN
ijassa-1442	170	3	process	process	NOUN
ijassa-1442	170	4	consists	consist	VERB
ijassa-1442	170	5	of	of	ADP
ijassa-1442	170	6	iterating	iterate	VERB
ijassa-1442	170	7	over	over	ADP
ijassa-1442	170	8	a	a	DET
ijassa-1442	170	9	number	number	NOUN
ijassa-1442	170	10	of	of	ADP
ijassa-1442	170	11	epochs	epoch	NOUN
ijassa-1442	170	12	,	,	PUNCT
ijassa-1442	170	13	each	each	DET
ijassa-1442	170	14	time	time	NOUN
ijassa-1442	170	15	selecting	select	VERB
ijassa-1442	170	16	a	a	DET
ijassa-1442	170	17	random	random	ADJ
ijassa-1442	170	18	batch	batch	NOUN
ijassa-1442	170	19	of	of	ADP
ijassa-1442	170	20	data	datum	NOUN
ijassa-1442	170	21	from	from	ADP
ijassa-1442	170	22	the	the	DET
ijassa-1442	170	23	training	training	NOUN
ijassa-1442	170	24	set	set	NOUN
ijassa-1442	170	25	.	.	PUNCT
ijassa-1442	171	1	the	the	DET
ijassa-1442	171	2	gradients	gradient	NOUN
ijassa-1442	171	3	for	for	ADP
ijassa-1442	171	4	each	each	DET
ijassa-1442	171	5	component	component	NOUN
ijassa-1442	171	6	are	be	AUX
ijassa-1442	171	7	computed	compute	VERB
ijassa-1442	171	8	and	and	CCONJ
ijassa-1442	171	9	clipped	clip	VERB
ijassa-1442	171	10	to	to	PART
ijassa-1442	171	11	ensure	ensure	VERB
ijassa-1442	171	12	that	that	SCONJ
ijassa-1442	171	13	they	they	PRON
ijassa-1442	171	14	do	do	AUX
ijassa-1442	171	15	not	not	PART
ijassa-1442	171	16	exceed	exceed	VERB
ijassa-1442	171	17	a	a	DET
ijassa-1442	171	18	certain	certain	ADJ
ijassa-1442	171	19	bound	bind	VERB
ijassa-1442	171	20	.	.	PUNCT
ijassa-1442	172	1	then	then	ADV
ijassa-1442	172	2	,	,	PUNCT
ijassa-1442	172	3	a	a	DET
ijassa-1442	172	4	noise	noise	NOUN
ijassa-1442	172	5	is	be	AUX
ijassa-1442	172	6	added	add	VERB
ijassa-1442	172	7	to	to	ADP
ijassa-1442	172	8	one	one	NUM
ijassa-1442	172	9	of	of	ADP
ijassa-1442	172	10	the	the	DET
ijassa-1442	172	11	components	component	NOUN
ijassa-1442	172	12	to	to	PART
ijassa-1442	172	13	achieve	achieve	VERB
ijassa-1442	172	14	differential	differential	ADJ
ijassa-1442	172	15	privacy	privacy	NOUN
ijassa-1442	172	16	.	.	PUNCT
ijassa-1442	173	1	finally	finally	ADV
ijassa-1442	173	2	,	,	PUNCT
ijassa-1442	173	3	the	the	DET
ijassa-1442	173	4	parameters	parameter	NOUN
ijassa-1442	173	5	of	of	ADP
ijassa-1442	173	6	the	the	DET
ijassa-1442	173	7	corresponding	corresponding	ADJ
ijassa-1442	173	8	component	component	NOUN
ijassa-1442	173	9	are	be	AUX
ijassa-1442	173	10	updated	update	VERB
ijassa-1442	173	11	by	by	ADP
ijassa-1442	173	12	performing	perform	VERB
ijassa-1442	173	13	stochastic	stochastic	ADJ
ijassa-1442	173	14	gradient	gradient	ADJ
ijassa-1442	173	15	descent	descent	NOUN
ijassa-1442	173	16	with	with	ADP
ijassa-1442	173	17	the	the	DET
ijassa-1442	173	18	computed	computed	ADJ
ijassa-1442	173	19	gradients	gradient	NOUN
ijassa-1442	173	20	.	.	PUNCT
ijassa-1442	174	1	this	this	DET
ijassa-1442	174	2	process	process	NOUN
ijassa-1442	174	3	is	be	AUX
ijassa-1442	174	4	repeated	repeat	VERB
ijassa-1442	174	5	until	until	SCONJ
ijassa-1442	174	6	the	the	DET
ijassa-1442	174	7	desired	desire	VERB
ijassa-1442	174	8	number	number	NOUN
ijassa-1442	174	9	of	of	ADP
ijassa-1442	174	10	epochs	epoch	NOUN
ijassa-1442	174	11	is	be	AUX
ijassa-1442	174	12	reached	reach	VERB
ijassa-1442	174	13	.	.	PUNCT
ijassa-1442	175	1	the	the	DET
ijassa-1442	175	2	training	training	NOUN
ijassa-1442	175	3	algorithm	algorithm	NOUN
ijassa-1442	175	4	of	of	ADP
ijassa-1442	175	5	laftr	laftr	NOUN
ijassa-1442	175	6	with	with	ADP
ijassa-1442	175	7	privacy	privacy	NOUN
ijassa-1442	175	8	preservation	preservation	NOUN
ijassa-1442	175	9	is	be	AUX
ijassa-1442	175	10	a	a	DET
ijassa-1442	175	11	crucial	crucial	ADJ
ijassa-1442	175	12	component	component	NOUN
ijassa-1442	175	13	of	of	ADP
ijassa-1442	175	14	this	this	DET
ijassa-1442	175	15	approach	approach	NOUN
ijassa-1442	175	16	,	,	PUNCT
ijassa-1442	175	17	allowing	allow	VERB
ijassa-1442	175	18	for	for	ADP
ijassa-1442	175	19	the	the	DET
ijassa-1442	175	20	training	training	NOUN
ijassa-1442	175	21	of	of	ADP
ijassa-1442	175	22	complex	complex	ADJ
ijassa-1442	175	23	models	model	NOUN
ijassa-1442	175	24	that	that	PRON
ijassa-1442	175	25	can	can	AUX
ijassa-1442	175	26	achieve	achieve	VERB
ijassa-1442	175	27	both	both	DET
ijassa-1442	175	28	fairness	fairness	NOUN
ijassa-1442	175	29	and	and	CCONJ
ijassa-1442	175	30	privacy	privacy	NOUN
ijassa-1442	175	31	.	.	PUNCT
ijassa-1442	176	1	4.4	4.4	NUM
ijassa-1442	176	2	.	.	PUNCT
ijassa-1442	177	1	evaluation	evaluation	NOUN
ijassa-1442	177	2	metrics	metric	NOUN
ijassa-1442	177	3	as	as	SCONJ
ijassa-1442	177	4	we	we	PRON
ijassa-1442	177	5	said	say	VERB
ijassa-1442	177	6	in	in	ADP
ijassa-1442	177	7	section	section	NOUN
ijassa-1442	177	8	4.3	4.3	NUM
ijassa-1442	177	9	,	,	PUNCT
ijassa-1442	177	10	we	we	PRON
ijassa-1442	177	11	try	try	VERB
ijassa-1442	177	12	to	to	PART
ijassa-1442	177	13	train	train	VERB
ijassa-1442	177	14	encoder	encoder	NOUN
ijassa-1442	177	15	which	which	PRON
ijassa-1442	177	16	will	will	AUX
ijassa-1442	177	17	give	give	VERB
ijassa-1442	177	18	reliable	reliable	ADJ
ijassa-1442	177	19	representation	representation	NOUN
ijassa-1442	177	20	.	.	PUNCT
ijassa-1442	178	1	training	training	NOUN
ijassa-1442	178	2	encoder	encoder	NOUN
ijassa-1442	178	3	several	several	ADJ
ijassa-1442	178	4	times	time	NOUN
ijassa-1442	178	5	and	and	CCONJ
ijassa-1442	178	6	taking	take	VERB
ijassa-1442	178	7	the	the	DET
ijassa-1442	178	8	outputs	output	NOUN
ijassa-1442	178	9	from	from	ADP
ijassa-1442	178	10	the	the	DET
ijassa-1442	178	11	encoder	encoder	NOUN
ijassa-1442	178	12	,	,	PUNCT
ijassa-1442	178	13	we	we	PRON
ijassa-1442	178	14	will	will	AUX
ijassa-1442	178	15	pass	pass	VERB
ijassa-1442	178	16	it	it	PRON
ijassa-1442	178	17	into	into	ADP
ijassa-1442	178	18	a	a	DET
ijassa-1442	178	19	simple	simple	ADJ
ijassa-1442	178	20	binary	binary	NOUN
ijassa-1442	178	21	classifier	classifier	NOUN
ijassa-1442	178	22	(	(	PUNCT
ijassa-1442	178	23	logistic	logistic	ADJ
ijassa-1442	178	24	regression	regression	NOUN
ijassa-1442	178	25	)	)	PUNCT
ijassa-1442	178	26	,	,	PUNCT
ijassa-1442	178	27	average	average	VERB
ijassa-1442	178	28	them	they	PRON
ijassa-1442	178	29	and	and	CCONJ
ijassa-1442	178	30	calculate	calculate	VERB
ijassa-1442	178	31	standard	standard	ADJ
ijassa-1442	178	32	deviation	deviation	NOUN
ijassa-1442	178	33	.	.	PUNCT
ijassa-1442	179	1	after	after	ADP
ijassa-1442	179	2	that	that	PRON
ijassa-1442	179	3	we	we	PRON
ijassa-1442	179	4	will	will	AUX
ijassa-1442	179	5	use	use	VERB
ijassa-1442	179	6	fairness	fairness	NOUN
ijassa-1442	179	7	metrics	metric	NOUN
ijassa-1442	179	8	which	which	PRON
ijassa-1442	179	9	was	be	AUX
ijassa-1442	179	10	mentioned	mention	VERB
ijassa-1442	179	11	in	in	ADP
ijassa-1442	179	12	section	section	NOUN
ijassa-1442	179	13	0	0	NUM
ijassa-1442	179	14	to	to	PART
ijassa-1442	179	15	evaluate	evaluate	VERB
ijassa-1442	179	16	these	these	DET
ijassa-1442	179	17	bias	bias	NOUN
ijassa-1442	179	18	-	-	PUNCT
ijassa-1442	179	19	mitigation	mitigation	NOUN
ijassa-1442	179	20	strategies	strategy	NOUN
ijassa-1442	179	21	.	.	PUNCT
ijassa-1442	180	1	also	also	ADV
ijassa-1442	180	2	,	,	PUNCT
ijassa-1442	180	3	we	we	PRON
ijassa-1442	180	4	will	will	AUX
ijassa-1442	180	5	measure	measure	VERB
ijassa-1442	180	6	accuracy	accuracy	NOUN
ijassa-1442	180	7	of	of	ADP
ijassa-1442	180	8	all	all	DET
ijassa-1442	180	9	models	model	NOUN
ijassa-1442	180	10	for	for	ADP
ijassa-1442	180	11	comparison	comparison	NOUN
ijassa-1442	180	12	with	with	ADP
ijassa-1442	180	13	bias	bias	NOUN
ijassa-1442	180	14	-	-	PUNCT
ijassa-1442	180	15	mitigation	mitigation	NOUN
ijassa-1442	180	16	strategies	strategy	NOUN
ijassa-1442	180	17	and	and	CCONJ
ijassa-1442	180	18	unfair	unfair	ADJ
ijassa-1442	180	19	strategies	strategy	NOUN
ijassa-1442	180	20	.	.	PUNCT
ijassa-1442	181	1	to	to	PART
ijassa-1442	181	2	evaluate	evaluate	VERB
ijassa-1442	181	3	accuracy	accuracy	NOUN
ijassa-1442	181	4	and	and	CCONJ
ijassa-1442	181	5	fair	fair	ADJ
ijassa-1442	181	6	metrics	metric	NOUN
ijassa-1442	181	7	we	we	PRON
ijassa-1442	181	8	will	will	AUX
ijassa-1442	181	9	use	use	VERB
ijassa-1442	181	10	logistic	logistic	ADJ
ijassa-1442	181	11	regression	regression	NOUN
ijassa-1442	181	12	.	.	PUNCT
ijassa-1442	182	1	logistic	logistic	ADJ
ijassa-1442	182	2	regression	regression	NOUN
ijassa-1442	182	3	will	will	AUX
ijassa-1442	182	4	learn	learn	VERB
ijassa-1442	182	5	on	on	ADP
ijassa-1442	182	6	generated	generate	VERB
ijassa-1442	182	7	by	by	ADP
ijassa-1442	182	8	encoder	encoder	NOUN
ijassa-1442	182	9	new	new	ADJ
ijassa-1442	182	10	data	datum	NOUN
ijassa-1442	182	11	several	several	ADJ
ijassa-1442	182	12	times	time	NOUN
ijassa-1442	182	13	and	and	CCONJ
ijassa-1442	182	14	return	return	VERB
ijassa-1442	182	15	mean	mean	NOUN
ijassa-1442	182	16	and	and	CCONJ
ijassa-1442	182	17	standard	standard	ADJ
ijassa-1442	182	18	deviation	deviation	NOUN
ijassa-1442	182	19	of	of	ADP
ijassa-1442	182	20	accuracy	accuracy	NOUN
ijassa-1442	182	21	,	,	PUNCT
ijassa-1442	182	22	difference	difference	NOUN
ijassa-1442	182	23	of	of	ADP
ijassa-1442	182	24	demographic	demographic	ADJ
ijassa-1442	182	25	parity	parity	NOUN
ijassa-1442	182	26	and	and	CCONJ
ijassa-1442	182	27	difference	difference	NOUN
ijassa-1442	182	28	of	of	ADP
ijassa-1442	182	29	equalized	equalize	VERB
ijassa-1442	182	30	odds	odd	NOUN
ijassa-1442	182	31	.	.	PUNCT
ijassa-1442	183	1	balancing	balance	VERB
ijassa-1442	183	2	accuracy	accuracy	NOUN
ijassa-1442	183	3	,	,	PUNCT
ijassa-1442	183	4	fairness	fairness	NOUN
ijassa-1442	183	5	and	and	CCONJ
ijassa-1442	183	6	privacy	privacy	NOUN
ijassa-1442	183	7	in	in	ADP
ijassa-1442	183	8	machine	machine	NOUN
ijassa-1442	183	9	learning	learning	NOUN
ijassa-1442	183	10	…	…	PUNCT
ijassa-1442	183	11	47	47	NUM
ijassa-1442	183	12	copyright	copyright	NOUN
ijassa-1442	183	13	©	©	PROPN
ijassa-1442	183	14	2023	2023	NUM
ijassa-1442	183	15	assa	assa	NOUN
ijassa-1442	183	16	.	.	PUNCT
ijassa-1442	184	1	adv	adv	PROPN
ijassa-1442	184	2	.	.	PUNCT
ijassa-1442	185	1	in	in	ADP
ijassa-1442	185	2	systems	system	NOUN
ijassa-1442	185	3	science	science	NOUN
ijassa-1442	185	4	and	and	CCONJ
ijassa-1442	185	5	appl	appl	NOUN
ijassa-1442	185	6	.	.	PUNCT
ijassa-1442	186	1	(	(	PUNCT
ijassa-1442	186	2	2023	2023	NUM
ijassa-1442	186	3	)	)	PUNCT
ijassa-1442	186	4	during	during	ADP
ijassa-1442	186	5	the	the	DET
ijassa-1442	186	6	training	training	NOUN
ijassa-1442	186	7	of	of	ADP
ijassa-1442	186	8	different	different	ADJ
ijassa-1442	186	9	model	model	NOUN
ijassa-1442	186	10	configurations	configuration	NOUN
ijassa-1442	186	11	,	,	PUNCT
ijassa-1442	186	12	the	the	DET
ijassa-1442	186	13	fair	fair	ADJ
ijassa-1442	186	14	metrics	metric	NOUN
ijassa-1442	186	15	and	and	CCONJ
ijassa-1442	186	16	accuracy	accuracy	NOUN
ijassa-1442	186	17	will	will	AUX
ijassa-1442	186	18	change	change	VERB
ijassa-1442	186	19	.	.	PUNCT
ijassa-1442	187	1	to	to	PART
ijassa-1442	187	2	understand	understand	VERB
ijassa-1442	187	3	advantages	advantage	NOUN
ijassa-1442	187	4	of	of	ADP
ijassa-1442	187	5	provided	provide	VERB
ijassa-1442	187	6	models	model	NOUN
ijassa-1442	187	7	we	we	PRON
ijassa-1442	187	8	need	need	VERB
ijassa-1442	187	9	to	to	PART
ijassa-1442	187	10	compare	compare	VERB
ijassa-1442	187	11	accuracy	accuracy	NOUN
ijassa-1442	187	12	-	-	PUNCT
ijassa-1442	187	13	fairness	fairness	NOUN
ijassa-1442	187	14	trade	trade	NOUN
ijassa-1442	187	15	-	-	PUNCT
ijassa-1442	187	16	off	off	NOUN
ijassa-1442	187	17	.	.	PUNCT
ijassa-1442	188	1	for	for	ADP
ijassa-1442	188	2	evaluation	evaluation	NOUN
ijassa-1442	188	3	trade	trade	NOUN
ijassa-1442	188	4	-	-	PUNCT
ijassa-1442	188	5	off	off	NOUN
ijassa-1442	188	6	we	we	PRON
ijassa-1442	188	7	will	will	AUX
ijassa-1442	188	8	use	use	VERB
ijassa-1442	188	9	next	next	ADJ
ijassa-1442	188	10	function	function	NOUN
ijassa-1442	188	11	:	:	PUNCT
ijassa-1442	188	12	where	where	SCONJ
ijassa-1442	188	13	accuracy	accuracy	NOUN
ijassa-1442	188	14	,	,	PUNCT
ijassa-1442	188	15	fair	fair	ADJ
ijassa-1442	188	16	metric	metric	ADJ
ijassa-1442	188	17	.	.	PUNCT
ijassa-1442	189	1	next	next	ADV
ijassa-1442	189	2	we	we	PRON
ijassa-1442	189	3	will	will	AUX
ijassa-1442	189	4	call	call	VERB
ijassa-1442	189	5	acc	acc	PROPN
ijassa-1442	189	6	/	/	SYM
ijassa-1442	189	7	fair	fair	ADJ
ijassa-1442	189	8	.	.	PUNCT
ijassa-1442	190	1	4.5	4.5	NUM
ijassa-1442	190	2	.	.	PUNCT
ijassa-1442	190	3	model	model	NOUN
ijassa-1442	190	4	and	and	CCONJ
ijassa-1442	190	5	hyperparameters	hyperparameter	NOUN
ijassa-1442	190	6	at	at	ADP
ijassa-1442	190	7	the	the	DET
ijassa-1442	190	8	outset	outset	NOUN
ijassa-1442	190	9	of	of	ADP
ijassa-1442	190	10	the	the	DET
ijassa-1442	190	11	experiment	experiment	NOUN
ijassa-1442	190	12	,	,	PUNCT
ijassa-1442	190	13	the	the	DET
ijassa-1442	190	14	initial	initial	ADJ
ijassa-1442	190	15	step	step	NOUN
ijassa-1442	190	16	was	be	AUX
ijassa-1442	190	17	to	to	PART
ijassa-1442	190	18	define	define	VERB
ijassa-1442	190	19	a	a	DET
ijassa-1442	190	20	set	set	NOUN
ijassa-1442	190	21	of	of	ADP
ijassa-1442	190	22	hyperparameters	hyperparameter	NOUN
ijassa-1442	190	23	that	that	PRON
ijassa-1442	190	24	remained	remain	VERB
ijassa-1442	190	25	constant	constant	ADJ
ijassa-1442	190	26	throughout	throughout	ADP
ijassa-1442	190	27	all	all	DET
ijassa-1442	190	28	subsequent	subsequent	ADJ
ijassa-1442	190	29	experiments	experiment	NOUN
ijassa-1442	190	30	.	.	PUNCT
ijassa-1442	191	1	hyperparameters	hyperparameter	NOUN
ijassa-1442	191	2	are	be	AUX
ijassa-1442	191	3	parameters	parameter	NOUN
ijassa-1442	191	4	that	that	PRON
ijassa-1442	191	5	can	can	AUX
ijassa-1442	191	6	not	not	PART
ijassa-1442	191	7	be	be	AUX
ijassa-1442	191	8	learned	learn	VERB
ijassa-1442	191	9	directly	directly	ADV
ijassa-1442	191	10	from	from	ADP
ijassa-1442	191	11	the	the	DET
ijassa-1442	191	12	training	training	NOUN
ijassa-1442	191	13	data	datum	NOUN
ijassa-1442	191	14	and	and	CCONJ
ijassa-1442	191	15	need	need	VERB
ijassa-1442	191	16	to	to	PART
ijassa-1442	191	17	be	be	AUX
ijassa-1442	191	18	set	set	VERB
ijassa-1442	191	19	manually	manually	ADV
ijassa-1442	191	20	before	before	ADP
ijassa-1442	191	21	the	the	DET
ijassa-1442	191	22	training	training	NOUN
ijassa-1442	191	23	process	process	NOUN
ijassa-1442	191	24	commences	commence	VERB
ijassa-1442	191	25	.	.	PUNCT
ijassa-1442	192	1	table	table	NOUN
ijassa-1442	192	2	1	1	NUM
ijassa-1442	192	3	.	.	PUNCT
ijassa-1442	192	4	model	model	PROPN
ijassa-1442	192	5	fixed	fix	VERB
ijassa-1442	192	6	hyperparameters	hyperparameter	NOUN
ijassa-1442	192	7	model	model	NOUN
ijassa-1442	192	8	hyperparameters	hyperparameter	NOUN
ijassa-1442	192	9	values	value	NOUN
ijassa-1442	192	10	encoder	encoder	NOUN
ijassa-1442	192	11	mlp	mlp	NOUN
ijassa-1442	192	12	depth	depth	NOUN
ijassa-1442	192	13	as	as	ADP
ijassa-1442	192	14	in	in	ADP
ijassa-1442	192	15	depth*[width	depth*[width	ADJ
ijassa-1442	192	16	]	]	PUNCT
ijassa-1442	192	17	2	2	NUM
ijassa-1442	192	18	layers	layer	NOUN
ijassa-1442	192	19	classifier	classifier	NOUN
ijassa-1442	192	20	mlp	mlp	NOUN
ijassa-1442	192	21	depth	depth	NOUN
ijassa-1442	192	22	as	as	ADP
ijassa-1442	192	23	in	in	ADP
ijassa-1442	192	24	depth*[width	depth*[width	ADJ
ijassa-1442	192	25	]	]	PUNCT
ijassa-1442	192	26	2	2	NUM
ijassa-1442	192	27	layers	layer	NOUN
ijassa-1442	192	28	encoder	encoder	NOUN
ijassa-1442	192	29	mlp	mlp	NOUN
ijassa-1442	192	30	width	width	VERB
ijassa-1442	192	31	32	32	NUM
ijassa-1442	192	32	neurons	neuron	NOUN
ijassa-1442	192	33	classifier	classifier	NOUN
ijassa-1442	192	34	mlp	mlp	PROPN
ijassa-1442	192	35	width	width	VERB
ijassa-1442	192	36	32	32	NUM
ijassa-1442	192	37	neurons	neuron	NOUN
ijassa-1442	192	38	latent	latent	NOUN
ijassa-1442	192	39	(	(	PUNCT
ijassa-1442	192	40	z	z	NOUN
ijassa-1442	192	41	)	)	PUNCT
ijassa-1442	192	42	space	space	NOUN
ijassa-1442	192	43	dimension	dimension	NOUN
ijassa-1442	192	44	8	8	NUM
ijassa-1442	192	45	neurons	neuron	NOUN
ijassa-1442	192	46	–	–	PUNCT
ijassa-1442	192	47	reconstruction	reconstruction	NOUN
ijassa-1442	192	48	loss	loss	NOUN
ijassa-1442	192	49	weight	weight	NOUN
ijassa-1442	192	50	0	0	NUM
ijassa-1442	192	51	–	–	PUNCT
ijassa-1442	192	52	prediction	prediction	NOUN
ijassa-1442	192	53	loss	loss	NOUN
ijassa-1442	192	54	weight	weight	NOUN
ijassa-1442	192	55	1	1	NUM
ijassa-1442	192	56	–	–	PUNCT
ijassa-1442	192	57	adversary	adversary	NOUN
ijassa-1442	192	58	loss	loss	NOUN
ijassa-1442	192	59	weight	weight	NOUN
ijassa-1442	192	60	1	1	NUM
ijassa-1442	192	61	activation	activation	NOUN
ijassa-1442	192	62	function	function	NOUN
ijassa-1442	192	63	in	in	ADP
ijassa-1442	192	64	hidden	hidden	ADJ
ijassa-1442	192	65	layers	layer	NOUN
ijassa-1442	192	66	in	in	ADP
ijassa-1442	192	67	autoencoder	autoencoder	NOUN
ijassa-1442	192	68	leakyrelu	leakyrelu	ADJ
ijassa-1442	192	69	activation	activation	NOUN
ijassa-1442	192	70	function	function	NOUN
ijassa-1442	192	71	in	in	ADP
ijassa-1442	192	72	hidden	hidden	ADJ
ijassa-1442	192	73	layers	layer	NOUN
ijassa-1442	192	74	in	in	ADP
ijassa-1442	192	75	classifier	classifier	NOUN
ijassa-1442	192	76	leakyrelu	leakyrelu	ADJ
ijassa-1442	192	77	activation	activation	NOUN
ijassa-1442	192	78	function	function	NOUN
ijassa-1442	192	79	in	in	ADP
ijassa-1442	192	80	hidden	hidden	ADJ
ijassa-1442	192	81	layers	layer	NOUN
ijassa-1442	192	82	in	in	ADP
ijassa-1442	192	83	adversary	adversary	NOUN
ijassa-1442	192	84	leakyrelu	leakyrelu	NOUN
ijassa-1442	192	85	activation	activation	NOUN
ijassa-1442	192	86	function	function	NOUN
ijassa-1442	192	87	after	after	ADP
ijassa-1442	192	88	last	last	ADJ
ijassa-1442	192	89	hidden	hide	VERB
ijassa-1442	192	90	layer	layer	NOUN
ijassa-1442	192	91	of	of	ADP
ijassa-1442	192	92	encoder	encoder	NOUN
ijassa-1442	192	93	leakyrelu	leakyrelu	NOUN
ijassa-1442	192	94	activation	activation	NOUN
ijassa-1442	192	95	function	function	VERB
ijassa-1442	192	96	after	after	ADP
ijassa-1442	192	97	last	last	ADJ
ijassa-1442	192	98	hidden	hide	VERB
ijassa-1442	192	99	layer	layer	NOUN
ijassa-1442	192	100	of	of	ADP
ijassa-1442	192	101	classifier	classifier	NOUN
ijassa-1442	192	102	sigmoid	sigmoid	NOUN
ijassa-1442	192	103	activation	activation	NOUN
ijassa-1442	192	104	function	function	NOUN
ijassa-1442	192	105	after	after	ADP
ijassa-1442	192	106	last	last	ADJ
ijassa-1442	192	107	hidden	hide	VERB
ijassa-1442	192	108	layer	layer	NOUN
ijassa-1442	192	109	of	of	ADP
ijassa-1442	192	110	adversary	adversary	NOUN
ijassa-1442	192	111	sigmoid	sigmoid	NOUN
ijassa-1442	192	112	in	in	ADP
ijassa-1442	192	113	table	table	NOUN
ijassa-1442	192	114	1	1	NUM
ijassa-1442	192	115	,	,	PUNCT
ijassa-1442	192	116	we	we	PRON
ijassa-1442	192	117	can	can	AUX
ijassa-1442	192	118	observe	observe	VERB
ijassa-1442	192	119	the	the	DET
ijassa-1442	192	120	various	various	ADJ
ijassa-1442	192	121	model	model	NOUN
ijassa-1442	192	122	hyperparameters	hyperparameter	NOUN
ijassa-1442	192	123	and	and	CCONJ
ijassa-1442	192	124	their	their	PRON
ijassa-1442	192	125	corresponding	correspond	VERB
ijassa-1442	192	126	values	value	NOUN
ijassa-1442	192	127	that	that	PRON
ijassa-1442	192	128	were	be	AUX
ijassa-1442	192	129	used	use	VERB
ijassa-1442	192	130	in	in	ADP
ijassa-1442	192	131	our	our	PRON
ijassa-1442	192	132	experiments	experiment	NOUN
ijassa-1442	192	133	.	.	PUNCT
ijassa-1442	193	1	we	we	PRON
ijassa-1442	193	2	trained	train	VERB
ijassa-1442	193	3	our	our	PRON
ijassa-1442	193	4	model	model	NOUN
ijassa-1442	193	5	without	without	ADP
ijassa-1442	193	6	taking	take	VERB
ijassa-1442	193	7	into	into	ADP
ijassa-1442	193	8	account	account	NOUN
ijassa-1442	193	9	the	the	DET
ijassa-1442	193	10	reconstruction	reconstruction	NOUN
ijassa-1442	193	11	loss	loss	NOUN
ijassa-1442	193	12	,	,	PUNCT
ijassa-1442	193	13	as	as	SCONJ
ijassa-1442	193	14	our	our	PRON
ijassa-1442	193	15	primary	primary	ADJ
ijassa-1442	193	16	goal	goal	NOUN
ijassa-1442	193	17	was	be	AUX
ijassa-1442	193	18	to	to	PART
ijassa-1442	193	19	obtain	obtain	VERB
ijassa-1442	193	20	a	a	DET
ijassa-1442	193	21	good	good	ADJ
ijassa-1442	193	22	representation	representation	NOUN
ijassa-1442	193	23	in	in	ADP
ijassa-1442	193	24	the	the	DET
ijassa-1442	193	25	latent	latent	NOUN
ijassa-1442	193	26	space	space	NOUN
ijassa-1442	193	27	.	.	PUNCT
ijassa-1442	194	1	therefore	therefore	ADV
ijassa-1442	194	2	,	,	PUNCT
ijassa-1442	194	3	we	we	PRON
ijassa-1442	194	4	did	do	AUX
ijassa-1442	194	5	not	not	PART
ijassa-1442	194	6	require	require	VERB
ijassa-1442	194	7	a	a	DET
ijassa-1442	194	8	good	good	ADJ
ijassa-1442	194	9	reconstruction	reconstruction	NOUN
ijassa-1442	194	10	of	of	ADP
ijassa-1442	194	11	input	input	NOUN
ijassa-1442	194	12	data	datum	NOUN
ijassa-1442	194	13	.	.	PUNCT
ijassa-1442	195	1	additionally	additionally	ADV
ijassa-1442	195	2	,	,	PUNCT
ijassa-1442	195	3	we	we	PRON
ijassa-1442	195	4	used	use	VERB
ijassa-1442	195	5	the	the	DET
ijassa-1442	195	6	same	same	ADJ
ijassa-1442	195	7	architecture	architecture	NOUN
ijassa-1442	195	8	for	for	ADP
ijassa-1442	195	9	all	all	DET
ijassa-1442	195	10	modules	module	NOUN
ijassa-1442	195	11	of	of	ADP
ijassa-1442	195	12	the	the	DET
ijassa-1442	195	13	network	network	NOUN
ijassa-1442	195	14	,	,	PUNCT
ijassa-1442	195	15	except	except	SCONJ
ijassa-1442	195	16	for	for	ADP
ijassa-1442	195	17	the	the	DET
ijassa-1442	195	18	activation	activation	NOUN
ijassa-1442	195	19	function	function	NOUN
ijassa-1442	195	20	after	after	ADP
ijassa-1442	195	21	the	the	DET
ijassa-1442	195	22	last	last	ADJ
ijassa-1442	195	23	hidden	hide	VERB
ijassa-1442	195	24	layer	layer	NOUN
ijassa-1442	195	25	of	of	ADP
ijassa-1442	195	26	the	the	DET
ijassa-1442	195	27	encoder	encoder	NOUN
ijassa-1442	195	28	.	.	PUNCT
ijassa-1442	196	1	this	this	DET
ijassa-1442	196	2	difference	difference	NOUN
ijassa-1442	196	3	in	in	ADP
ijassa-1442	196	4	the	the	DET
ijassa-1442	196	5	activation	activation	NOUN
ijassa-1442	196	6	function	function	NOUN
ijassa-1442	196	7	was	be	AUX
ijassa-1442	196	8	necessary	necessary	ADJ
ijassa-1442	196	9	since	since	SCONJ
ijassa-1442	196	10	the	the	DET
ijassa-1442	196	11	encoder	encoder	NOUN
ijassa-1442	196	12	generates	generate	VERB
ijassa-1442	196	13	a	a	DET
ijassa-1442	196	14	new	new	ADJ
ijassa-1442	196	15	representation	representation	NOUN
ijassa-1442	196	16	of	of	ADP
ijassa-1442	196	17	input	input	NOUN
ijassa-1442	196	18	data	datum	NOUN
ijassa-1442	196	19	whereas	whereas	SCONJ
ijassa-1442	196	20	the	the	DET
ijassa-1442	196	21	classifier	classifier	NOUN
ijassa-1442	196	22	and	and	CCONJ
ijassa-1442	196	23	adversary	adversary	NOUN
ijassa-1442	196	24	try	try	VERB
ijassa-1442	196	25	to	to	PART
ijassa-1442	196	26	predict	predict	VERB
ijassa-1442	196	27	label	label	NOUN
ijassa-1442	196	28	or	or	CCONJ
ijassa-1442	196	29	attribute	attribute	NOUN
ijassa-1442	196	30	,	,	PUNCT
ijassa-1442	196	31	which	which	PRON
ijassa-1442	196	32	have	have	VERB
ijassa-1442	196	33	binary	binary	ADJ
ijassa-1442	196	34	nature	nature	NOUN
ijassa-1442	196	35	.	.	PUNCT
ijassa-1442	197	1	the	the	DET
ijassa-1442	197	2	choice	choice	NOUN
ijassa-1442	197	3	of	of	ADP
ijassa-1442	197	4	parameters	parameter	NOUN
ijassa-1442	197	5	in	in	ADP
ijassa-1442	197	6	the	the	DET
ijassa-1442	197	7	model	model	NOUN
ijassa-1442	197	8	was	be	AUX
ijassa-1442	197	9	based	base	VERB
ijassa-1442	197	10	on	on	ADP
ijassa-1442	197	11	the	the	DET
ijassa-1442	197	12	findings	finding	NOUN
ijassa-1442	197	13	from	from	ADP
ijassa-1442	197	14	prior	prior	ADJ
ijassa-1442	197	15	research	research	NOUN
ijassa-1442	197	16	,	,	PUNCT
ijassa-1442	197	17	particularly	particularly	ADV
ijassa-1442	197	18	[	[	X
ijassa-1442	197	19	21	21	NUM
ijassa-1442	197	20	]	]	PUNCT
ijassa-1442	197	21	.	.	PUNCT
ijassa-1442	198	1	the	the	DET
ijassa-1442	198	2	model	model	NOUN
ijassa-1442	198	3	architecture	architecture	NOUN
ijassa-1442	198	4	was	be	AUX
ijassa-1442	198	5	configured	configure	VERB
ijassa-1442	198	6	to	to	PART
ijassa-1442	198	7	have	have	VERB
ijassa-1442	198	8	a	a	DET
ijassa-1442	198	9	two	two	NUM
ijassa-1442	198	10	-	-	PUNCT
ijassa-1442	198	11	layer	layer	NOUN
ijassa-1442	198	12	multi	multi	ADJ
ijassa-1442	198	13	-	-	ADJ
ijassa-1442	198	14	layer	layer	ADJ
ijassa-1442	198	15	perceptron	perceptron	NOUN
ijassa-1442	198	16	(	(	PUNCT
ijassa-1442	198	17	mlp	mlp	PROPN
ijassa-1442	199	1	[	[	X
ijassa-1442	199	2	22	22	NUM
ijassa-1442	199	3	]	]	PUNCT
ijassa-1442	199	4	)	)	PUNCT
ijassa-1442	199	5	for	for	ADP
ijassa-1442	199	6	both	both	CCONJ
ijassa-1442	199	7	the	the	DET
ijassa-1442	199	8	encoder	encoder	NOUN
ijassa-1442	199	9	and	and	CCONJ
ijassa-1442	199	10	classifier	classifier	NOUN
ijassa-1442	199	11	,	,	PUNCT
ijassa-1442	199	12	with	with	ADP
ijassa-1442	199	13	a	a	DET
ijassa-1442	199	14	width	width	NOUN
ijassa-1442	199	15	of	of	ADP
ijassa-1442	199	16	32	32	NUM
ijassa-1442	199	17	neurons	neuron	NOUN
ijassa-1442	199	18	in	in	ADP
ijassa-1442	199	19	each	each	DET
ijassa-1442	199	20	layer	layer	NOUN
ijassa-1442	199	21	,	,	PUNCT
ijassa-1442	199	22	following	follow	VERB
ijassa-1442	199	23	the	the	DET
ijassa-1442	199	24	recommendation	recommendation	NOUN
ijassa-1442	199	25	from	from	ADP
ijassa-1442	199	26	[	[	X
ijassa-1442	199	27	21	21	NUM
ijassa-1442	199	28	]	]	PUNCT
ijassa-1442	199	29	.	.	PUNCT
ijassa-1442	200	1	the	the	DET
ijassa-1442	200	2	adversary	adversary	NOUN
ijassa-1442	200	3	module	module	NOUN
ijassa-1442	200	4	was	be	AUX
ijassa-1442	200	5	set	set	VERB
ijassa-1442	200	6	up	up	ADP
ijassa-1442	200	7	in	in	ADP
ijassa-1442	200	8	two	two	NUM
ijassa-1442	200	9	different	different	ADJ
ijassa-1442	200	10	configurations	configuration	NOUN
ijassa-1442	200	11	.	.	PUNCT
ijassa-1442	201	1	the	the	DET
ijassa-1442	201	2	latent	latent	NOUN
ijassa-1442	201	3	space	space	NOUN
ijassa-1442	201	4	dimension	dimension	NOUN
ijassa-1442	201	5	was	be	AUX
ijassa-1442	201	6	set	set	VERB
ijassa-1442	201	7	to	to	ADP
ijassa-1442	201	8	8	8	NUM
ijassa-1442	201	9	neurons	neuron	NOUN
ijassa-1442	201	10	.	.	PUNCT
ijassa-1442	202	1	having	having	AUX
ijassa-1442	202	2	completed	complete	VERB
ijassa-1442	202	3	the	the	DET
ijassa-1442	202	4	previous	previous	ADJ
ijassa-1442	202	5	step	step	NOUN
ijassa-1442	202	6	,	,	PUNCT
ijassa-1442	202	7	the	the	DET
ijassa-1442	202	8	subsequent	subsequent	ADJ
ijassa-1442	202	9	action	action	NOUN
ijassa-1442	202	10	is	be	AUX
ijassa-1442	202	11	to	to	PART
ijassa-1442	202	12	establish	establish	VERB
ijassa-1442	202	13	the	the	DET
ijassa-1442	202	14	values	value	NOUN
ijassa-1442	202	15	of	of	ADP
ijassa-1442	202	16	the	the	DET
ijassa-1442	202	17	training	training	NOUN
ijassa-1442	202	18	parameters	parameter	NOUN
ijassa-1442	202	19	.	.	PUNCT
ijassa-1442	203	1	these	these	DET
ijassa-1442	203	2	parameters	parameter	NOUN
ijassa-1442	203	3	are	be	AUX
ijassa-1442	203	4	essential	essential	ADJ
ijassa-1442	203	5	in	in	ADP
ijassa-1442	203	6	controlling	control	VERB
ijassa-1442	203	7	the	the	DET
ijassa-1442	203	8	learning	learning	NOUN
ijassa-1442	203	9	process	process	NOUN
ijassa-1442	203	10	and	and	CCONJ
ijassa-1442	203	11	determining	determine	VERB
ijassa-1442	203	12	the	the	DET
ijassa-1442	203	13	behavior	behavior	NOUN
ijassa-1442	203	14	of	of	ADP
ijassa-1442	203	15	the	the	DET
ijassa-1442	203	16	model	model	NOUN
ijassa-1442	203	17	during	during	ADP
ijassa-1442	203	18	the	the	DET
ijassa-1442	203	19	training	training	NOUN
ijassa-1442	203	20	phase	phase	NOUN
ijassa-1442	203	21	.	.	PUNCT
ijassa-1442	204	1	the	the	DET
ijassa-1442	204	2	selection	selection	NOUN
ijassa-1442	204	3	of	of	ADP
ijassa-1442	204	4	suitable	suitable	ADJ
ijassa-1442	204	5	values	value	NOUN
ijassa-1442	204	6	for	for	ADP
ijassa-1442	204	7	these	these	DET
ijassa-1442	204	8	parameters	parameter	NOUN
ijassa-1442	204	9	is	be	AUX
ijassa-1442	204	10	a	a	DET
ijassa-1442	204	11	crucial	crucial	ADJ
ijassa-1442	204	12	process	process	NOUN
ijassa-1442	204	13	as	as	SCONJ
ijassa-1442	204	14	it	it	PRON
ijassa-1442	204	15	can	can	AUX
ijassa-1442	204	16	significantly	significantly	ADV
ijassa-1442	204	17	influence	influence	VERB
ijassa-1442	204	18	the	the	DET
ijassa-1442	204	19	performance	performance	NOUN
ijassa-1442	204	20	of	of	ADP
ijassa-1442	204	21	the	the	DET
ijassa-1442	204	22	model	model	NOUN
ijassa-1442	204	23	.	.	PUNCT
ijassa-1442	205	1	after	after	ADP
ijassa-1442	205	2	determining	determine	VERB
ijassa-1442	205	3	the	the	DET
ijassa-1442	205	4	appropriate	appropriate	ADJ
ijassa-1442	205	5	values	value	NOUN
ijassa-1442	205	6	for	for	ADP
ijassa-1442	205	7	the	the	DET
ijassa-1442	205	8	training	training	NOUN
ijassa-1442	205	9	parameters	parameter	NOUN
ijassa-1442	205	10	,	,	PUNCT
ijassa-1442	205	11	they	they	PRON
ijassa-1442	205	12	were	be	AUX
ijassa-1442	205	13	fixed	fix	VERB
ijassa-1442	205	14	and	and	CCONJ
ijassa-1442	205	15	used	use	VERB
ijassa-1442	205	16	throughout	throughout	ADP
ijassa-1442	205	17	the	the	DET
ijassa-1442	205	18	training	training	NOUN
ijassa-1442	205	19	process	process	NOUN
ijassa-1442	205	20	to	to	PART
ijassa-1442	205	21	optimize	optimize	VERB
ijassa-1442	205	22	the	the	DET
ijassa-1442	205	23	model	model	NOUN
ijassa-1442	205	24	's	's	PART
ijassa-1442	205	25	performance	performance	NOUN
ijassa-1442	205	26	on	on	ADP
ijassa-1442	205	27	the	the	DET
ijassa-1442	205	28	given	give	VERB
ijassa-1442	205	29	task	task	NOUN
ijassa-1442	205	30	.	.	PUNCT
ijassa-1442	206	1	notably	notably	ADV
ijassa-1442	206	2	,	,	PUNCT
ijassa-1442	206	3	these	these	DET
ijassa-1442	206	4	parameters	parameter	NOUN
ijassa-1442	206	5	were	be	AUX
ijassa-1442	206	6	carefully	carefully	ADV
ijassa-1442	206	7	chosen	choose	VERB
ijassa-1442	206	8	to	to	PART
ijassa-1442	206	9	produce	produce	VERB
ijassa-1442	206	10	results	result	NOUN
ijassa-1442	206	11	that	that	PRON
ijassa-1442	206	12	could	could	AUX
ijassa-1442	206	13	be	be	AUX
ijassa-1442	206	14	compared	compare	VERB
ijassa-1442	206	15	to	to	ADP
ijassa-1442	206	16	those	those	PRON
ijassa-1442	206	17	reported	report	VERB
ijassa-1442	206	18	in	in	ADP
ijassa-1442	206	19	a	a	DET
ijassa-1442	206	20	previous	previous	ADJ
ijassa-1442	206	21	study	study	NOUN
ijassa-1442	206	22	[	[	X
ijassa-1442	206	23	17	17	NUM
ijassa-1442	206	24	]	]	PUNCT
ijassa-1442	206	25	.	.	PUNCT
ijassa-1442	207	1	the	the	DET
ijassa-1442	207	2	process	process	NOUN
ijassa-1442	207	3	of	of	ADP
ijassa-1442	207	4	defining	define	VERB
ijassa-1442	207	5	these	these	DET
ijassa-1442	207	6	constant	constant	ADJ
ijassa-1442	207	7	training	training	NOUN
ijassa-1442	207	8	parameters	parameter	NOUN
ijassa-1442	207	9	is	be	AUX
ijassa-1442	207	10	complex	complex	ADJ
ijassa-1442	207	11	,	,	PUNCT
ijassa-1442	207	12	and	and	CCONJ
ijassa-1442	207	13	various	various	ADJ
ijassa-1442	207	14	factors	factor	NOUN
ijassa-1442	207	15	must	must	AUX
ijassa-1442	207	16	be	be	AUX
ijassa-1442	207	17	considered	consider	VERB
ijassa-1442	207	18	.	.	PUNCT
ijassa-1442	208	1	the	the	DET
ijassa-1442	208	2	size	size	NOUN
ijassa-1442	208	3	of	of	ADP
ijassa-1442	208	4	the	the	DET
ijassa-1442	208	5	dataset	dataset	NOUN
ijassa-1442	208	6	,	,	PUNCT
ijassa-1442	208	7	the	the	DET
ijassa-1442	208	8	complexity	complexity	NOUN
ijassa-1442	208	9	of	of	ADP
ijassa-1442	208	10	the	the	DET
ijassa-1442	208	11	model	model	NOUN
ijassa-1442	208	12	,	,	PUNCT
ijassa-1442	208	13	and	and	CCONJ
ijassa-1442	208	14	the	the	DET
ijassa-1442	208	15	available	available	ADJ
ijassa-1442	208	16	computational	computational	ADJ
ijassa-1442	208	17	resources	resource	NOUN
ijassa-1442	208	18	–	–	PUNCT
ijassa-1442	208	19	factors	factor	NOUN
ijassa-1442	208	20	which	which	PRON
ijassa-1442	208	21	were	be	AUX
ijassa-1442	208	22	taking	take	VERB
ijassa-1442	208	23	into	into	ADP
ijassa-1442	208	24	account	account	NOUN
ijassa-1442	208	25	during	during	ADP
ijassa-1442	208	26	empirical	empirical	ADJ
ijassa-1442	208	27	48	48	NUM
ijassa-1442	208	28	a.	a.	NOUN
ijassa-1442	208	29	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	208	30	,	,	PUNCT
ijassa-1442	208	31	r.	r.	PROPN
ijassa-1442	208	32	sabitov	sabitov	PROPN
ijassa-1442	208	33	,	,	PUNCT
ijassa-1442	208	34	g.	g.	PROPN
ijassa-1442	208	35	smirnova	smirnova	PROPN
ijassa-1442	208	36	,	,	PUNCT
ijassa-1442	208	37	sh	sh	PROPN
ijassa-1442	208	38	.	.	PUNCT
ijassa-1442	208	39	sabitov	sabitov	PROPN
ijassa-1442	208	40	copyright	copyright	NOUN
ijassa-1442	208	41	©	©	PROPN
ijassa-1442	208	42	2023	2023	NUM
ijassa-1442	208	43	assa	assa	PROPN
ijassa-1442	208	44	adv	adv	PROPN
ijassa-1442	208	45	.	.	PUNCT
ijassa-1442	209	1	in	in	ADP
ijassa-1442	209	2	systems	system	NOUN
ijassa-1442	209	3	science	science	NOUN
ijassa-1442	209	4	and	and	CCONJ
ijassa-1442	209	5	appl	appl	NOUN
ijassa-1442	209	6	.	.	PUNCT
ijassa-1442	210	1	(	(	PUNCT
ijassa-1442	210	2	2023	2023	NUM
ijassa-1442	210	3	)	)	PUNCT
ijassa-1442	210	4	choosing	choose	VERB
ijassa-1442	210	5	hyperparameters	hyperparameter	NOUN
ijassa-1442	210	6	.	.	PUNCT
ijassa-1442	211	1	the	the	DET
ijassa-1442	211	2	most	most	ADV
ijassa-1442	211	3	important	important	ADJ
ijassa-1442	211	4	hyperparameters	hyperparameter	NOUN
ijassa-1442	211	5	which	which	PRON
ijassa-1442	211	6	affect	affect	VERB
ijassa-1442	211	7	to	to	ADP
ijassa-1442	211	8	results	result	NOUN
ijassa-1442	211	9	learning	learn	VERB
ijassa-1442	211	10	rate	rate	NOUN
ijassa-1442	211	11	,	,	PUNCT
ijassa-1442	211	12	and	and	CCONJ
ijassa-1442	211	13	number	number	NOUN
ijassa-1442	211	14	of	of	ADP
ijassa-1442	211	15	epochs	epoch	NOUN
ijassa-1442	211	16	,	,	PUNCT
ijassa-1442	211	17	optimizer	optimizer	NOUN
ijassa-1442	211	18	.	.	PUNCT
ijassa-1442	212	1	finding	find	VERB
ijassa-1442	212	2	the	the	DET
ijassa-1442	212	3	best	good	ADJ
ijassa-1442	212	4	combination	combination	NOUN
ijassa-1442	212	5	of	of	ADP
ijassa-1442	212	6	these	these	DET
ijassa-1442	212	7	parameters	parameter	NOUN
ijassa-1442	212	8	helps	help	VERB
ijassa-1442	212	9	achieve	achieve	VERB
ijassa-1442	212	10	optimal	optimal	ADJ
ijassa-1442	212	11	results	result	NOUN
ijassa-1442	212	12	.	.	PUNCT
ijassa-1442	213	1	once	once	ADV
ijassa-1442	213	2	the	the	DET
ijassa-1442	213	3	appropriate	appropriate	ADJ
ijassa-1442	213	4	values	value	NOUN
ijassa-1442	213	5	for	for	ADP
ijassa-1442	213	6	the	the	DET
ijassa-1442	213	7	training	training	NOUN
ijassa-1442	213	8	parameters	parameter	NOUN
ijassa-1442	213	9	have	have	AUX
ijassa-1442	213	10	been	be	AUX
ijassa-1442	213	11	determined	determine	VERB
ijassa-1442	213	12	,	,	PUNCT
ijassa-1442	213	13	they	they	PRON
ijassa-1442	213	14	are	be	AUX
ijassa-1442	213	15	fixed	fix	VERB
ijassa-1442	213	16	and	and	CCONJ
ijassa-1442	213	17	used	use	VERB
ijassa-1442	213	18	throughout	throughout	ADP
ijassa-1442	213	19	the	the	DET
ijassa-1442	213	20	training	training	NOUN
ijassa-1442	213	21	process	process	NOUN
ijassa-1442	213	22	to	to	PART
ijassa-1442	213	23	optimize	optimize	VERB
ijassa-1442	213	24	the	the	DET
ijassa-1442	213	25	model	model	NOUN
ijassa-1442	213	26	's	's	PART
ijassa-1442	213	27	performance	performance	NOUN
ijassa-1442	213	28	on	on	ADP
ijassa-1442	213	29	the	the	DET
ijassa-1442	213	30	given	give	VERB
ijassa-1442	213	31	task	task	NOUN
ijassa-1442	213	32	.	.	PUNCT
ijassa-1442	214	1	regular	regular	ADJ
ijassa-1442	214	2	monitoring	monitoring	NOUN
ijassa-1442	214	3	and	and	CCONJ
ijassa-1442	214	4	tuning	tuning	NOUN
ijassa-1442	214	5	of	of	ADP
ijassa-1442	214	6	these	these	DET
ijassa-1442	214	7	parameters	parameter	NOUN
ijassa-1442	214	8	may	may	AUX
ijassa-1442	214	9	also	also	ADV
ijassa-1442	214	10	be	be	AUX
ijassa-1442	214	11	required	require	VERB
ijassa-1442	214	12	during	during	ADP
ijassa-1442	214	13	the	the	DET
ijassa-1442	214	14	training	training	NOUN
ijassa-1442	214	15	process	process	NOUN
ijassa-1442	214	16	to	to	PART
ijassa-1442	214	17	ensure	ensure	VERB
ijassa-1442	214	18	that	that	SCONJ
ijassa-1442	214	19	the	the	DET
ijassa-1442	214	20	model	model	NOUN
ijassa-1442	214	21	continues	continue	VERB
ijassa-1442	214	22	to	to	PART
ijassa-1442	214	23	improve	improve	VERB
ijassa-1442	214	24	its	its	PRON
ijassa-1442	214	25	performance	performance	NOUN
ijassa-1442	214	26	.	.	PUNCT
ijassa-1442	215	1	in	in	ADP
ijassa-1442	215	2	some	some	DET
ijassa-1442	215	3	cases	case	NOUN
ijassa-1442	215	4	generally	generally	ADV
ijassa-1442	215	5	founded	found	VERB
ijassa-1442	215	6	hyperparameters	hyperparameter	NOUN
ijassa-1442	215	7	can	can	AUX
ijassa-1442	215	8	not	not	PART
ijassa-1442	215	9	provide	provide	VERB
ijassa-1442	215	10	satisfiable	satisfiable	ADJ
ijassa-1442	215	11	results	result	NOUN
ijassa-1442	215	12	.	.	PUNCT
ijassa-1442	216	1	this	this	DET
ijassa-1442	216	2	iterative	iterative	NOUN
ijassa-1442	216	3	process	process	NOUN
ijassa-1442	216	4	involves	involve	VERB
ijassa-1442	216	5	observing	observe	VERB
ijassa-1442	216	6	the	the	DET
ijassa-1442	216	7	model	model	NOUN
ijassa-1442	216	8	's	's	PART
ijassa-1442	216	9	performance	performance	NOUN
ijassa-1442	216	10	during	during	ADP
ijassa-1442	216	11	training	training	NOUN
ijassa-1442	216	12	,	,	PUNCT
ijassa-1442	216	13	making	make	VERB
ijassa-1442	216	14	adjustments	adjustment	NOUN
ijassa-1442	216	15	to	to	ADP
ijassa-1442	216	16	the	the	DET
ijassa-1442	216	17	parameters	parameter	NOUN
ijassa-1442	216	18	,	,	PUNCT
ijassa-1442	216	19	and	and	CCONJ
ijassa-1442	216	20	retraining	retrain	VERB
ijassa-1442	216	21	the	the	DET
ijassa-1442	216	22	model	model	NOUN
ijassa-1442	216	23	to	to	PART
ijassa-1442	216	24	ensure	ensure	VERB
ijassa-1442	216	25	that	that	SCONJ
ijassa-1442	216	26	it	it	PRON
ijassa-1442	216	27	is	be	AUX
ijassa-1442	216	28	optimized	optimize	VERB
ijassa-1442	216	29	for	for	ADP
ijassa-1442	216	30	the	the	DET
ijassa-1442	216	31	task	task	NOUN
ijassa-1442	216	32	at	at	ADP
ijassa-1442	216	33	hand	hand	NOUN
ijassa-1442	216	34	.	.	PUNCT
ijassa-1442	217	1	table	table	NOUN
ijassa-1442	217	2	2	2	NUM
ijassa-1442	217	3	training	training	NOUN
ijassa-1442	217	4	fixed	fix	VERB
ijassa-1442	217	5	parameters	parameter	NOUN
ijassa-1442	217	6	training	train	VERB
ijassa-1442	217	7	parameters	parameter	NOUN
ijassa-1442	217	8	values	value	VERB
ijassa-1442	217	9	max	max	PROPN
ijassa-1442	217	10	gradient	gradient	PROPN
ijassa-1442	217	11	norm	norm	NOUN
ijassa-1442	217	12	in	in	ADP
ijassa-1442	217	13	encoder	encoder	NOUN
ijassa-1442	217	14	10	10	NUM
ijassa-1442	217	15	max	max	PROPN
ijassa-1442	217	16	gradient	gradient	PROPN
ijassa-1442	217	17	norm	norm	NOUN
ijassa-1442	217	18	in	in	ADP
ijassa-1442	217	19	classifier	classifier	PROPN
ijassa-1442	217	20	10	10	NUM
ijassa-1442	217	21	max	max	PROPN
ijassa-1442	217	22	gradient	gradient	PROPN
ijassa-1442	217	23	norm	norm	NOUN
ijassa-1442	217	24	in	in	ADP
ijassa-1442	217	25	adversary	adversary	NOUN
ijassa-1442	217	26	10	10	NUM
ijassa-1442	217	27	encoder	encoder	NOUN
ijassa-1442	217	28	/	/	SYM
ijassa-1442	217	29	classifier	classifier	NOUN
ijassa-1442	217	30	optimizer	optimizer	NOUN
ijassa-1442	217	31	nadam	nadam	PROPN
ijassa-1442	217	32	adversary	adversary	NOUN
ijassa-1442	217	33	optimizer	optimizer	NOUN
ijassa-1442	217	34	nadam	nadam	PROPN
ijassa-1442	217	35	encoder	encoder	NOUN
ijassa-1442	217	36	/	/	SYM
ijassa-1442	217	37	classifier	classifier	NOUN
ijassa-1442	217	38	learning	learn	VERB
ijassa-1442	217	39	rate	rate	NOUN
ijassa-1442	217	40	scheduler	scheduler	NOUN
ijassa-1442	217	41	polynomiallr(2	polynomiallr(2	NOUN
ijassa-1442	217	42	)	)	PUNCT
ijassa-1442	217	43	adversary	adversary	NOUN
ijassa-1442	217	44	learning	learn	VERB
ijassa-1442	217	45	rate	rate	NOUN
ijassa-1442	217	46	scheduler	scheduler	NOUN
ijassa-1442	217	47	polynomiallr(2	polynomiallr(2	NOUN
ijassa-1442	217	48	)	)	PUNCT
ijassa-1442	217	49	the	the	DET
ijassa-1442	217	50	table	table	NOUN
ijassa-1442	217	51	2	2	NUM
ijassa-1442	217	52	provided	provide	VERB
ijassa-1442	217	53	outlines	outline	NOUN
ijassa-1442	217	54	the	the	DET
ijassa-1442	217	55	specific	specific	ADJ
ijassa-1442	217	56	training	training	NOUN
ijassa-1442	217	57	parameters	parameter	NOUN
ijassa-1442	217	58	and	and	CCONJ
ijassa-1442	217	59	their	their	PRON
ijassa-1442	217	60	corresponding	corresponding	ADJ
ijassa-1442	217	61	values	value	NOUN
ijassa-1442	217	62	that	that	PRON
ijassa-1442	217	63	were	be	AUX
ijassa-1442	217	64	used	use	VERB
ijassa-1442	217	65	during	during	ADP
ijassa-1442	217	66	the	the	DET
ijassa-1442	217	67	training	training	NOUN
ijassa-1442	217	68	process	process	NOUN
ijassa-1442	217	69	.	.	PUNCT
ijassa-1442	218	1	the	the	DET
ijassa-1442	218	2	values	value	NOUN
ijassa-1442	218	3	were	be	AUX
ijassa-1442	218	4	carefully	carefully	ADV
ijassa-1442	218	5	selected	select	VERB
ijassa-1442	218	6	based	base	VERB
ijassa-1442	218	7	on	on	ADP
ijassa-1442	218	8	various	various	ADJ
ijassa-1442	218	9	factors	factor	NOUN
ijassa-1442	218	10	,	,	PUNCT
ijassa-1442	218	11	such	such	ADJ
ijassa-1442	218	12	as	as	ADP
ijassa-1442	218	13	the	the	DET
ijassa-1442	218	14	size	size	NOUN
ijassa-1442	218	15	of	of	ADP
ijassa-1442	218	16	the	the	DET
ijassa-1442	218	17	dataset	dataset	NOUN
ijassa-1442	218	18	and	and	CCONJ
ijassa-1442	218	19	the	the	DET
ijassa-1442	218	20	complexity	complexity	NOUN
ijassa-1442	218	21	of	of	ADP
ijassa-1442	218	22	the	the	DET
ijassa-1442	218	23	model	model	NOUN
ijassa-1442	218	24	.	.	PUNCT
ijassa-1442	219	1	the	the	DET
ijassa-1442	219	2	maximum	maximum	PROPN
ijassa-1442	219	3	gradient	gradient	NOUN
ijassa-1442	219	4	norm	norm	NOUN
ijassa-1442	219	5	in	in	ADP
ijassa-1442	219	6	the	the	DET
ijassa-1442	219	7	encoder	encoder	NOUN
ijassa-1442	219	8	,	,	PUNCT
ijassa-1442	219	9	classifier	classifier	NOUN
ijassa-1442	219	10	,	,	PUNCT
ijassa-1442	219	11	and	and	CCONJ
ijassa-1442	219	12	adversary	adversary	NOUN
ijassa-1442	219	13	was	be	AUX
ijassa-1442	219	14	set	set	VERB
ijassa-1442	219	15	to	to	ADP
ijassa-1442	219	16	a	a	DET
ijassa-1442	219	17	value	value	NOUN
ijassa-1442	219	18	of	of	ADP
ijassa-1442	219	19	10	10	NUM
ijassa-1442	219	20	.	.	PUNCT
ijassa-1442	220	1	this	this	DET
ijassa-1442	220	2	parameter	parameter	NOUN
ijassa-1442	220	3	controls	control	VERB
ijassa-1442	220	4	the	the	DET
ijassa-1442	220	5	maximum	maximum	ADJ
ijassa-1442	220	6	magnitude	magnitude	NOUN
ijassa-1442	220	7	of	of	ADP
ijassa-1442	220	8	the	the	DET
ijassa-1442	220	9	gradients	gradient	NOUN
ijassa-1442	220	10	during	during	ADP
ijassa-1442	220	11	the	the	DET
ijassa-1442	220	12	training	training	NOUN
ijassa-1442	220	13	process	process	NOUN
ijassa-1442	220	14	,	,	PUNCT
ijassa-1442	220	15	preventing	prevent	VERB
ijassa-1442	220	16	the	the	DET
ijassa-1442	220	17	model	model	NOUN
ijassa-1442	220	18	from	from	ADP
ijassa-1442	220	19	diverging	diverge	VERB
ijassa-1442	220	20	or	or	CCONJ
ijassa-1442	220	21	becoming	become	VERB
ijassa-1442	220	22	unstable	unstable	ADJ
ijassa-1442	220	23	.	.	PUNCT
ijassa-1442	221	1	the	the	DET
ijassa-1442	221	2	optimization	optimization	NOUN
ijassa-1442	221	3	algorithm	algorithm	NOUN
ijassa-1442	221	4	used	use	VERB
ijassa-1442	221	5	for	for	ADP
ijassa-1442	221	6	both	both	CCONJ
ijassa-1442	221	7	the	the	DET
ijassa-1442	221	8	encoder	encoder	NOUN
ijassa-1442	221	9	and	and	CCONJ
ijassa-1442	221	10	classifier	classifier	NOUN
ijassa-1442	221	11	was	be	AUX
ijassa-1442	221	12	nadam	nadam	PROPN
ijassa-1442	221	13	,	,	PUNCT
ijassa-1442	221	14	while	while	SCONJ
ijassa-1442	221	15	the	the	DET
ijassa-1442	221	16	adversary	adversary	NOUN
ijassa-1442	221	17	used	use	VERB
ijassa-1442	221	18	the	the	DET
ijassa-1442	221	19	same	same	ADJ
ijassa-1442	221	20	algorithm	algorithm	NOUN
ijassa-1442	221	21	with	with	ADP
ijassa-1442	221	22	modifications	modification	NOUN
ijassa-1442	221	23	to	to	PART
ijassa-1442	221	24	ensure	ensure	VERB
ijassa-1442	221	25	differential	differential	ADJ
ijassa-1442	221	26	privacy	privacy	NOUN
ijassa-1442	221	27	.	.	PUNCT
ijassa-1442	222	1	nadam	nadam	PROPN
ijassa-1442	222	2	was	be	AUX
ijassa-1442	222	3	selected	select	VERB
ijassa-1442	222	4	over	over	ADP
ijassa-1442	222	5	other	other	ADJ
ijassa-1442	222	6	popular	popular	ADJ
ijassa-1442	222	7	optimization	optimization	NOUN
ijassa-1442	222	8	algorithms	algorithm	NOUN
ijassa-1442	222	9	due	due	ADP
ijassa-1442	222	10	to	to	ADP
ijassa-1442	222	11	its	its	PRON
ijassa-1442	222	12	superior	superior	ADJ
ijassa-1442	222	13	performance	performance	NOUN
ijassa-1442	222	14	in	in	ADP
ijassa-1442	222	15	handling	handle	VERB
ijassa-1442	222	16	noisy	noisy	ADJ
ijassa-1442	222	17	or	or	CCONJ
ijassa-1442	222	18	sparse	sparse	ADJ
ijassa-1442	222	19	gradients	gradient	NOUN
ijassa-1442	222	20	.	.	PUNCT
ijassa-1442	223	1	nadam	nadam	PROPN
ijassa-1442	223	2	is	be	AUX
ijassa-1442	223	3	a	a	DET
ijassa-1442	223	4	variant	variant	NOUN
ijassa-1442	223	5	of	of	ADP
ijassa-1442	223	6	the	the	DET
ijassa-1442	223	7	adam	adam	PROPN
ijassa-1442	223	8	optimization	optimization	NOUN
ijassa-1442	223	9	algorithm	algorithm	NOUN
ijassa-1442	223	10	that	that	PRON
ijassa-1442	223	11	combines	combine	VERB
ijassa-1442	223	12	the	the	DET
ijassa-1442	223	13	benefits	benefit	NOUN
ijassa-1442	223	14	of	of	ADP
ijassa-1442	223	15	adaptive	adaptive	ADJ
ijassa-1442	223	16	learning	learning	NOUN
ijassa-1442	223	17	rates	rate	NOUN
ijassa-1442	223	18	and	and	CCONJ
ijassa-1442	223	19	momentumbased	momentumbase	VERB
ijassa-1442	223	20	optimization	optimization	NOUN
ijassa-1442	223	21	techniques	technique	NOUN
ijassa-1442	223	22	[	[	X
ijassa-1442	223	23	23	23	NUM
ijassa-1442	223	24	]	]	PUNCT
ijassa-1442	223	25	.	.	PUNCT
ijassa-1442	224	1	it	it	PRON
ijassa-1442	224	2	has	have	AUX
ijassa-1442	224	3	been	be	AUX
ijassa-1442	224	4	shown	show	VERB
ijassa-1442	224	5	to	to	PART
ijassa-1442	224	6	outperform	outperform	VERB
ijassa-1442	224	7	other	other	ADJ
ijassa-1442	224	8	popular	popular	ADJ
ijassa-1442	224	9	optimization	optimization	NOUN
ijassa-1442	224	10	algorithms	algorithm	NOUN
ijassa-1442	224	11	such	such	ADJ
ijassa-1442	224	12	as	as	ADP
ijassa-1442	224	13	adagrad	adagrad	ADJ
ijassa-1442	224	14	,	,	PUNCT
ijassa-1442	224	15	rmsprop	rmsprop	NOUN
ijassa-1442	224	16	,	,	PUNCT
ijassa-1442	224	17	and	and	CCONJ
ijassa-1442	224	18	adam	adam	PROPN
ijassa-1442	224	19	.	.	PUNCT
ijassa-1442	225	1	in	in	ADP
ijassa-1442	225	2	detail	detail	NOUN
ijassa-1442	225	3	,	,	PUNCT
ijassa-1442	225	4	dp	dp	PROPN
ijassa-1442	225	5	-	-	PUNCT
ijassa-1442	225	6	nadam	nadam	PROPN
ijassa-1442	225	7	works	work	VERB
ijassa-1442	225	8	similarly	similarly	ADV
ijassa-1442	225	9	to	to	ADP
ijassa-1442	225	10	dp	dp	NOUN
ijassa-1442	225	11	-	-	PUNCT
ijassa-1442	225	12	sgd	sgd	ADJ
ijassa-1442	225	13	,	,	PUNCT
ijassa-1442	225	14	with	with	ADP
ijassa-1442	225	15	some	some	DET
ijassa-1442	225	16	modifications	modification	NOUN
ijassa-1442	225	17	that	that	PRON
ijassa-1442	225	18	introduce	introduce	VERB
ijassa-1442	225	19	the	the	DET
ijassa-1442	225	20	nadam	nadam	PROPN
ijassa-1442	225	21	algorithm	algorithm	NOUN
ijassa-1442	225	22	itself	itself	PRON
ijassa-1442	225	23	.	.	PUNCT
ijassa-1442	226	1	these	these	DET
ijassa-1442	226	2	modifications	modification	NOUN
ijassa-1442	226	3	include	include	VERB
ijassa-1442	226	4	the	the	DET
ijassa-1442	226	5	calculation	calculation	NOUN
ijassa-1442	226	6	of	of	ADP
ijassa-1442	226	7	the	the	DET
ijassa-1442	226	8	adaptive	adaptive	ADJ
ijassa-1442	226	9	learning	learning	NOUN
ijassa-1442	226	10	rates	rate	NOUN
ijassa-1442	226	11	and	and	CCONJ
ijassa-1442	226	12	momentum	momentum	NOUN
ijassa-1442	226	13	parameters	parameter	NOUN
ijassa-1442	226	14	,	,	PUNCT
ijassa-1442	226	15	which	which	PRON
ijassa-1442	226	16	are	be	AUX
ijassa-1442	226	17	adjusted	adjust	VERB
ijassa-1442	226	18	based	base	VERB
ijassa-1442	226	19	on	on	ADP
ijassa-1442	226	20	the	the	DET
ijassa-1442	226	21	first	first	ADJ
ijassa-1442	226	22	and	and	CCONJ
ijassa-1442	226	23	second	second	ADJ
ijassa-1442	226	24	moments	moment	NOUN
ijassa-1442	226	25	of	of	ADP
ijassa-1442	226	26	the	the	DET
ijassa-1442	226	27	gradient	gradient	NOUN
ijassa-1442	226	28	,	,	PUNCT
ijassa-1442	226	29	as	as	ADV
ijassa-1442	226	30	well	well	ADV
ijassa-1442	226	31	as	as	ADP
ijassa-1442	226	32	the	the	DET
ijassa-1442	226	33	inclusion	inclusion	NOUN
ijassa-1442	226	34	of	of	ADP
ijassa-1442	226	35	noise	noise	NOUN
ijassa-1442	226	36	to	to	PART
ijassa-1442	226	37	ensure	ensure	VERB
ijassa-1442	226	38	differential	differential	ADJ
ijassa-1442	226	39	privacy	privacy	NOUN
ijassa-1442	226	40	.	.	PUNCT
ijassa-1442	227	1	the	the	DET
ijassa-1442	227	2	choice	choice	NOUN
ijassa-1442	227	3	of	of	ADP
ijassa-1442	227	4	nadam	nadam	PROPN
ijassa-1442	227	5	over	over	ADP
ijassa-1442	227	6	sgd	sgd	PROPN
ijassa-1442	227	7	was	be	AUX
ijassa-1442	227	8	made	make	VERB
ijassa-1442	227	9	based	base	VERB
ijassa-1442	227	10	on	on	ADP
ijassa-1442	227	11	its	its	PRON
ijassa-1442	227	12	superior	superior	ADJ
ijassa-1442	227	13	performance	performance	NOUN
ijassa-1442	227	14	on	on	ADP
ijassa-1442	227	15	the	the	DET
ijassa-1442	227	16	given	give	VERB
ijassa-1442	227	17	task	task	NOUN
ijassa-1442	227	18	,	,	PUNCT
ijassa-1442	227	19	as	as	ADV
ijassa-1442	227	20	well	well	ADV
ijassa-1442	227	21	as	as	ADP
ijassa-1442	227	22	its	its	PRON
ijassa-1442	227	23	ability	ability	NOUN
ijassa-1442	227	24	to	to	PART
ijassa-1442	227	25	handle	handle	VERB
ijassa-1442	227	26	noisy	noisy	ADJ
ijassa-1442	227	27	or	or	CCONJ
ijassa-1442	227	28	sparse	sparse	ADJ
ijassa-1442	227	29	gradients	gradient	NOUN
ijassa-1442	227	30	that	that	PRON
ijassa-1442	227	31	are	be	AUX
ijassa-1442	227	32	common	common	ADJ
ijassa-1442	227	33	in	in	ADP
ijassa-1442	227	34	differential	differential	ADJ
ijassa-1442	227	35	privacy	privacy	NOUN
ijassa-1442	227	36	settings	setting	NOUN
ijassa-1442	227	37	.	.	PUNCT
ijassa-1442	228	1	furthermore	furthermore	ADV
ijassa-1442	228	2	,	,	PUNCT
ijassa-1442	228	3	the	the	DET
ijassa-1442	228	4	use	use	NOUN
ijassa-1442	228	5	of	of	ADP
ijassa-1442	228	6	dp	dp	PROPN
ijassa-1442	228	7	-	-	PUNCT
ijassa-1442	228	8	nadam	nadam	PROPN
ijassa-1442	228	9	provides	provide	VERB
ijassa-1442	228	10	additional	additional	ADJ
ijassa-1442	228	11	benefits	benefit	NOUN
ijassa-1442	228	12	such	such	ADJ
ijassa-1442	228	13	as	as	ADP
ijassa-1442	228	14	faster	fast	ADJ
ijassa-1442	228	15	convergence	convergence	NOUN
ijassa-1442	228	16	rates	rate	NOUN
ijassa-1442	228	17	.	.	PUNCT
ijassa-1442	229	1	the	the	DET
ijassa-1442	229	2	learning	learning	NOUN
ijassa-1442	229	3	rate	rate	NOUN
ijassa-1442	229	4	scheduler	scheduler	NOUN
ijassa-1442	229	5	used	use	VERB
ijassa-1442	229	6	for	for	ADP
ijassa-1442	229	7	both	both	CCONJ
ijassa-1442	229	8	the	the	DET
ijassa-1442	229	9	encoder	encoder	NOUN
ijassa-1442	229	10	and	and	CCONJ
ijassa-1442	229	11	classifier	classifier	NOUN
ijassa-1442	229	12	was	be	AUX
ijassa-1442	229	13	polynomiallr(2	polynomiallr(2	NOUN
ijassa-1442	229	14	)	)	PUNCT
ijassa-1442	229	15	,	,	PUNCT
ijassa-1442	229	16	which	which	PRON
ijassa-1442	229	17	gradually	gradually	ADV
ijassa-1442	229	18	reduces	reduce	VERB
ijassa-1442	229	19	the	the	DET
ijassa-1442	229	20	learning	learning	NOUN
ijassa-1442	229	21	rate	rate	NOUN
ijassa-1442	229	22	quadratically	quadratically	ADV
ijassa-1442	229	23	over	over	ADP
ijassa-1442	229	24	the	the	DET
ijassa-1442	229	25	course	course	NOUN
ijassa-1442	229	26	of	of	ADP
ijassa-1442	229	27	the	the	DET
ijassa-1442	229	28	training	training	NOUN
ijassa-1442	229	29	process	process	NOUN
ijassa-1442	229	30	to	to	PART
ijassa-1442	229	31	prevent	prevent	VERB
ijassa-1442	229	32	the	the	DET
ijassa-1442	229	33	model	model	NOUN
ijassa-1442	229	34	from	from	ADP
ijassa-1442	229	35	overfitting	overfitte	VERB
ijassa-1442	229	36	to	to	ADP
ijassa-1442	229	37	the	the	DET
ijassa-1442	229	38	training	training	NOUN
ijassa-1442	229	39	data	datum	NOUN
ijassa-1442	229	40	.	.	PUNCT
ijassa-1442	230	1	similarly	similarly	ADV
ijassa-1442	230	2	,	,	PUNCT
ijassa-1442	230	3	the	the	DET
ijassa-1442	230	4	adversary	adversary	NOUN
ijassa-1442	230	5	also	also	ADV
ijassa-1442	230	6	used	use	VERB
ijassa-1442	230	7	the	the	DET
ijassa-1442	230	8	same	same	ADJ
ijassa-1442	230	9	scheduler	scheduler	NOUN
ijassa-1442	230	10	.	.	PUNCT
ijassa-1442	231	1	it	it	PRON
ijassa-1442	231	2	is	be	AUX
ijassa-1442	231	3	worth	worth	ADJ
ijassa-1442	231	4	noting	note	VERB
ijassa-1442	231	5	that	that	SCONJ
ijassa-1442	231	6	the	the	DET
ijassa-1442	231	7	choice	choice	NOUN
ijassa-1442	231	8	of	of	ADP
ijassa-1442	231	9	parameters	parameter	NOUN
ijassa-1442	231	10	was	be	AUX
ijassa-1442	231	11	not	not	PART
ijassa-1442	231	12	solely	solely	ADV
ijassa-1442	231	13	based	base	VERB
ijassa-1442	231	14	on	on	ADP
ijassa-1442	231	15	the	the	DET
ijassa-1442	231	16	findings	finding	NOUN
ijassa-1442	231	17	from	from	ADP
ijassa-1442	231	18	[	[	X
ijassa-1442	231	19	21	21	NUM
ijassa-1442	231	20	]	]	PUNCT
ijassa-1442	231	21	,	,	PUNCT
ijassa-1442	231	22	as	as	SCONJ
ijassa-1442	231	23	modifications	modification	NOUN
ijassa-1442	231	24	were	be	AUX
ijassa-1442	231	25	made	make	VERB
ijassa-1442	231	26	to	to	PART
ijassa-1442	231	27	ensure	ensure	VERB
ijassa-1442	231	28	the	the	DET
ijassa-1442	231	29	model	model	NOUN
ijassa-1442	231	30	could	could	AUX
ijassa-1442	231	31	achieve	achieve	VERB
ijassa-1442	231	32	similar	similar	ADJ
ijassa-1442	231	33	results	result	NOUN
ijassa-1442	231	34	as	as	SCONJ
ijassa-1442	231	35	reported	report	VERB
ijassa-1442	231	36	in	in	ADP
ijassa-1442	231	37	both	both	PRON
ijassa-1442	231	38	[	[	X
ijassa-1442	231	39	21	21	NUM
ijassa-1442	231	40	]	]	PUNCT
ijassa-1442	231	41	and	and	CCONJ
ijassa-1442	231	42	[	[	X
ijassa-1442	231	43	17	17	NUM
ijassa-1442	231	44	]	]	PUNCT
ijassa-1442	231	45	.	.	PUNCT
ijassa-1442	232	1	while	while	SCONJ
ijassa-1442	232	2	[	[	X
ijassa-1442	232	3	21	21	NUM
ijassa-1442	232	4	]	]	PUNCT
ijassa-1442	232	5	provided	provide	VERB
ijassa-1442	232	6	valuable	valuable	ADJ
ijassa-1442	232	7	insights	insight	NOUN
ijassa-1442	232	8	into	into	ADP
ijassa-1442	232	9	the	the	DET
ijassa-1442	232	10	choice	choice	NOUN
ijassa-1442	232	11	of	of	ADP
ijassa-1442	232	12	architecture	architecture	NOUN
ijassa-1442	232	13	,	,	PUNCT
ijassa-1442	232	14	latent	latent	ADJ
ijassa-1442	232	15	space	space	NOUN
ijassa-1442	232	16	dimension	dimension	NOUN
ijassa-1442	232	17	,	,	PUNCT
ijassa-1442	232	18	and	and	CCONJ
ijassa-1442	232	19	the	the	DET
ijassa-1442	232	20	adversary	adversary	NOUN
ijassa-1442	232	21	module	module	NOUN
ijassa-1442	232	22	configurations	configuration	NOUN
ijassa-1442	232	23	,	,	PUNCT
ijassa-1442	232	24	[	[	X
ijassa-1442	232	25	17	17	NUM
ijassa-1442	232	26	]	]	PUNCT
ijassa-1442	232	27	provided	provide	VERB
ijassa-1442	232	28	guidance	guidance	NOUN
ijassa-1442	232	29	on	on	ADP
ijassa-1442	232	30	the	the	DET
ijassa-1442	232	31	selection	selection	NOUN
ijassa-1442	232	32	of	of	ADP
ijassa-1442	232	33	the	the	DET
ijassa-1442	232	34	optimization	optimization	NOUN
ijassa-1442	232	35	algorithm	algorithm	NOUN
ijassa-1442	232	36	and	and	CCONJ
ijassa-1442	232	37	its	its	PRON
ijassa-1442	232	38	modifications	modification	NOUN
ijassa-1442	232	39	to	to	PART
ijassa-1442	232	40	ensure	ensure	VERB
ijassa-1442	232	41	differential	differential	ADJ
ijassa-1442	232	42	privacy	privacy	NOUN
ijassa-1442	232	43	.	.	PUNCT
ijassa-1442	233	1	the	the	DET
ijassa-1442	233	2	modifications	modification	NOUN
ijassa-1442	233	3	made	make	VERB
ijassa-1442	233	4	to	to	ADP
ijassa-1442	233	5	the	the	DET
ijassa-1442	233	6	optimization	optimization	NOUN
ijassa-1442	233	7	algorithm	algorithm	NOUN
ijassa-1442	233	8	were	be	AUX
ijassa-1442	233	9	necessary	necessary	ADJ
ijassa-1442	233	10	to	to	PART
ijassa-1442	233	11	achieve	achieve	VERB
ijassa-1442	233	12	differential	differential	ADJ
ijassa-1442	233	13	privacy	privacy	NOUN
ijassa-1442	233	14	while	while	SCONJ
ijassa-1442	233	15	maintaining	maintain	VERB
ijassa-1442	233	16	the	the	DET
ijassa-1442	233	17	model	model	NOUN
ijassa-1442	233	18	's	's	PART
ijassa-1442	233	19	performance	performance	NOUN
ijassa-1442	233	20	.	.	PUNCT
ijassa-1442	234	1	it	it	PRON
ijassa-1442	234	2	should	should	AUX
ijassa-1442	234	3	be	be	AUX
ijassa-1442	234	4	noted	note	VERB
ijassa-1442	234	5	that	that	SCONJ
ijassa-1442	234	6	even	even	ADV
ijassa-1442	234	7	with	with	ADP
ijassa-1442	234	8	the	the	DET
ijassa-1442	234	9	use	use	NOUN
ijassa-1442	234	10	of	of	ADP
ijassa-1442	234	11	dp	dp	NOUN
ijassa-1442	234	12	-	-	PUNCT
ijassa-1442	234	13	nadam	nadam	PROPN
ijassa-1442	234	14	,	,	PUNCT
ijassa-1442	234	15	the	the	DET
ijassa-1442	234	16	learning	learning	NOUN
ijassa-1442	234	17	rate	rate	NOUN
ijassa-1442	234	18	still	still	ADV
ijassa-1442	234	19	had	have	VERB
ijassa-1442	234	20	to	to	PART
ijassa-1442	234	21	be	be	AUX
ijassa-1442	234	22	increased	increase	VERB
ijassa-1442	234	23	dramatically	dramatically	ADV
ijassa-1442	234	24	(	(	PUNCT
ijassa-1442	234	25	~0.1	~0.1	NOUN
ijassa-1442	234	26	-	-	PUNCT
ijassa-1442	234	27	0.15	0.15	NUM
ijassa-1442	234	28	)	)	PUNCT
ijassa-1442	234	29	to	to	PART
ijassa-1442	234	30	achieve	achieve	VERB
ijassa-1442	234	31	the	the	DET
ijassa-1442	234	32	desired	desire	VERB
ijassa-1442	234	33	level	level	NOUN
ijassa-1442	234	34	of	of	ADP
ijassa-1442	234	35	performance	performance	NOUN
ijassa-1442	234	36	.	.	PUNCT
ijassa-1442	235	1	despite	despite	SCONJ
ijassa-1442	235	2	the	the	DET
ijassa-1442	235	3	need	need	NOUN
ijassa-1442	235	4	to	to	PART
ijassa-1442	235	5	increase	increase	VERB
ijassa-1442	235	6	the	the	DET
ijassa-1442	235	7	learning	learning	NOUN
ijassa-1442	235	8	rate	rate	NOUN
ijassa-1442	235	9	dramatically	dramatically	ADV
ijassa-1442	235	10	,	,	PUNCT
ijassa-1442	235	11	the	the	DET
ijassa-1442	235	12	model	model	NOUN
ijassa-1442	235	13	was	be	AUX
ijassa-1442	235	14	able	able	ADJ
ijassa-1442	235	15	to	to	PART
ijassa-1442	235	16	achieve	achieve	VERB
ijassa-1442	235	17	the	the	DET
ijassa-1442	235	18	desired	desire	VERB
ijassa-1442	235	19	level	level	NOUN
ijassa-1442	235	20	of	of	ADP
ijassa-1442	235	21	performance	performance	NOUN
ijassa-1442	235	22	balancing	balancing	NOUN
ijassa-1442	235	23	accuracy	accuracy	NOUN
ijassa-1442	235	24	,	,	PUNCT
ijassa-1442	235	25	fairness	fairness	NOUN
ijassa-1442	235	26	and	and	CCONJ
ijassa-1442	235	27	privacy	privacy	NOUN
ijassa-1442	235	28	in	in	ADP
ijassa-1442	235	29	machine	machine	NOUN
ijassa-1442	235	30	learning	learning	NOUN
ijassa-1442	235	31	…	…	PUNCT
ijassa-1442	235	32	49	49	NUM
ijassa-1442	235	33	copyright	copyright	NOUN
ijassa-1442	235	34	©	©	PROPN
ijassa-1442	235	35	2023	2023	NUM
ijassa-1442	235	36	assa	assa	NOUN
ijassa-1442	235	37	.	.	PUNCT
ijassa-1442	236	1	adv	adv	PROPN
ijassa-1442	236	2	.	.	PUNCT
ijassa-1442	237	1	in	in	ADP
ijassa-1442	237	2	systems	system	NOUN
ijassa-1442	237	3	science	science	NOUN
ijassa-1442	237	4	and	and	CCONJ
ijassa-1442	237	5	appl	appl	NOUN
ijassa-1442	237	6	.	.	PUNCT
ijassa-1442	238	1	(	(	PUNCT
ijassa-1442	238	2	2023	2023	NUM
ijassa-1442	238	3	)	)	PUNCT
ijassa-1442	238	4	without	without	ADP
ijassa-1442	238	5	sacrificing	sacrifice	VERB
ijassa-1442	238	6	its	its	PRON
ijassa-1442	238	7	stability	stability	NOUN
ijassa-1442	238	8	or	or	CCONJ
ijassa-1442	238	9	accuracy	accuracy	NOUN
ijassa-1442	238	10	.	.	PUNCT
ijassa-1442	239	1	overall	overall	ADV
ijassa-1442	239	2	,	,	PUNCT
ijassa-1442	239	3	the	the	DET
ijassa-1442	239	4	parameters	parameter	NOUN
ijassa-1442	239	5	were	be	AUX
ijassa-1442	239	6	carefully	carefully	ADV
ijassa-1442	239	7	selected	select	VERB
ijassa-1442	239	8	based	base	VERB
ijassa-1442	239	9	on	on	ADP
ijassa-1442	239	10	a	a	DET
ijassa-1442	239	11	mixture	mixture	NOUN
ijassa-1442	239	12	of	of	ADP
ijassa-1442	239	13	insights	insight	NOUN
ijassa-1442	239	14	from	from	ADP
ijassa-1442	239	15	both	both	PRON
ijassa-1442	239	16	[	[	X
ijassa-1442	239	17	21	21	NUM
ijassa-1442	239	18	]	]	PUNCT
ijassa-1442	239	19	and	and	CCONJ
ijassa-1442	239	20	[	[	X
ijassa-1442	239	21	17	17	NUM
ijassa-1442	239	22	]	]	PUNCT
ijassa-1442	239	23	,	,	PUNCT
ijassa-1442	239	24	with	with	ADP
ijassa-1442	239	25	modifications	modification	NOUN
ijassa-1442	239	26	to	to	PART
ijassa-1442	239	27	ensure	ensure	VERB
ijassa-1442	239	28	that	that	SCONJ
ijassa-1442	239	29	the	the	DET
ijassa-1442	239	30	model	model	NOUN
ijassa-1442	239	31	could	could	AUX
ijassa-1442	239	32	achieve	achieve	VERB
ijassa-1442	239	33	the	the	DET
ijassa-1442	239	34	desired	desire	VERB
ijassa-1442	239	35	level	level	NOUN
ijassa-1442	239	36	of	of	ADP
ijassa-1442	239	37	performance	performance	NOUN
ijassa-1442	239	38	while	while	SCONJ
ijassa-1442	239	39	maintaining	maintain	VERB
ijassa-1442	239	40	differential	differential	ADJ
ijassa-1442	239	41	privacy	privacy	NOUN
ijassa-1442	239	42	.	.	PUNCT
ijassa-1442	240	1	additionally	additionally	ADV
ijassa-1442	240	2	,	,	PUNCT
ijassa-1442	240	3	based	base	VERB
ijassa-1442	240	4	on	on	ADP
ijassa-1442	240	5	a	a	DET
ijassa-1442	240	6	large	large	ADJ
ijassa-1442	240	7	number	number	NOUN
ijassa-1442	240	8	of	of	ADP
ijassa-1442	240	9	parameter	parameter	NOUN
ijassa-1442	240	10	tuning	tuning	NOUN
ijassa-1442	240	11	attempts	attempt	NOUN
ijassa-1442	240	12	,	,	PUNCT
ijassa-1442	240	13	it	it	PRON
ijassa-1442	240	14	was	be	AUX
ijassa-1442	240	15	discovered	discover	VERB
ijassa-1442	240	16	that	that	SCONJ
ijassa-1442	240	17	using	use	VERB
ijassa-1442	240	18	a	a	DET
ijassa-1442	240	19	larger	large	ADJ
ijassa-1442	240	20	batch	batch	NOUN
ijassa-1442	240	21	size	size	NOUN
ijassa-1442	240	22	improves	improve	VERB
ijassa-1442	240	23	model	model	NOUN
ijassa-1442	240	24	stability	stability	NOUN
ijassa-1442	240	25	.	.	PUNCT
ijassa-1442	241	1	therefore	therefore	ADV
ijassa-1442	241	2	,	,	PUNCT
ijassa-1442	241	3	the	the	DET
ijassa-1442	241	4	maximum	maximum	ADJ
ijassa-1442	241	5	feasible	feasible	ADJ
ijassa-1442	241	6	batch	batch	NOUN
ijassa-1442	241	7	size	size	NOUN
ijassa-1442	241	8	was	be	AUX
ijassa-1442	241	9	used	use	VERB
ijassa-1442	241	10	for	for	ADP
ijassa-1442	241	11	training	training	NOUN
ijassa-1442	241	12	,	,	PUNCT
ijassa-1442	241	13	which	which	PRON
ijassa-1442	241	14	could	could	AUX
ijassa-1442	241	15	fit	fit	VERB
ijassa-1442	241	16	in	in	ADP
ijassa-1442	241	17	vram	vram	NOUN
ijassa-1442	241	18	.	.	PUNCT
ijassa-1442	242	1	for	for	ADP
ijassa-1442	242	2	the	the	DET
ijassa-1442	242	3	adult	adult	NOUN
ijassa-1442	242	4	dataset	dataset	NOUN
ijassa-1442	242	5	,	,	PUNCT
ijassa-1442	242	6	the	the	DET
ijassa-1442	242	7	entire	entire	ADJ
ijassa-1442	242	8	dataset	dataset	NOUN
ijassa-1442	242	9	was	be	AUX
ijassa-1442	242	10	used	use	VERB
ijassa-1442	242	11	,	,	PUNCT
ijassa-1442	242	12	for	for	ADP
ijassa-1442	242	13	the	the	DET
ijassa-1442	242	14	german	german	ADJ
ijassa-1442	242	15	dataset	dataset	NOUN
ijassa-1442	242	16	,	,	PUNCT
ijassa-1442	242	17	the	the	DET
ijassa-1442	242	18	entire	entire	ADJ
ijassa-1442	242	19	dataset	dataset	NOUN
ijassa-1442	242	20	was	be	AUX
ijassa-1442	242	21	used	use	VERB
ijassa-1442	242	22	,	,	PUNCT
ijassa-1442	242	23	and	and	CCONJ
ijassa-1442	242	24	for	for	ADP
ijassa-1442	242	25	celeba	celeba	PROPN
ijassa-1442	242	26	,	,	PUNCT
ijassa-1442	242	27	20,000	20,000	NUM
ijassa-1442	242	28	samples	sample	NOUN
ijassa-1442	242	29	were	be	AUX
ijassa-1442	242	30	used	use	VERB
ijassa-1442	242	31	.	.	PUNCT
ijassa-1442	243	1	empirically	empirically	ADV
ijassa-1442	243	2	,	,	PUNCT
ijassa-1442	243	3	it	it	PRON
ijassa-1442	243	4	has	have	AUX
ijassa-1442	243	5	been	be	AUX
ijassa-1442	243	6	observed	observe	VERB
ijassa-1442	243	7	that	that	SCONJ
ijassa-1442	243	8	the	the	DET
ijassa-1442	243	9	model	model	NOUN
ijassa-1442	243	10	may	may	AUX
ijassa-1442	243	11	cease	cease	VERB
ijassa-1442	243	12	to	to	PART
ijassa-1442	243	13	be	be	AUX
ijassa-1442	243	14	adequate	adequate	ADJ
ijassa-1442	243	15	under	under	ADP
ijassa-1442	243	16	certain	certain	ADJ
ijassa-1442	243	17	conditions	condition	NOUN
ijassa-1442	243	18	.	.	PUNCT
ijassa-1442	244	1	therefore	therefore	ADV
ijassa-1442	244	2	,	,	PUNCT
ijassa-1442	244	3	after	after	ADP
ijassa-1442	244	4	training	train	VERB
ijassa-1442	244	5	the	the	DET
ijassa-1442	244	6	model	model	NOUN
ijassa-1442	244	7	,	,	PUNCT
ijassa-1442	244	8	a	a	DET
ijassa-1442	244	9	validation	validation	NOUN
ijassa-1442	244	10	of	of	ADP
ijassa-1442	244	11	its	its	PRON
ijassa-1442	244	12	adequacy	adequacy	NOUN
ijassa-1442	244	13	was	be	AUX
ijassa-1442	244	14	conducted	conduct	VERB
ijassa-1442	244	15	.	.	PUNCT
ijassa-1442	245	1	the	the	DET
ijassa-1442	245	2	classifier	classifier	NOUN
ijassa-1442	245	3	within	within	ADP
ijassa-1442	245	4	the	the	DET
ijassa-1442	245	5	neural	neural	ADJ
ijassa-1442	245	6	model	model	NOUN
ijassa-1442	245	7	should	should	AUX
ijassa-1442	245	8	yield	yield	VERB
ijassa-1442	245	9	accuracy	accuracy	NOUN
ijassa-1442	245	10	values	value	NOUN
ijassa-1442	245	11	above	above	ADP
ijassa-1442	245	12	50	50	NUM
ijassa-1442	245	13	%	%	NOUN
ijassa-1442	245	14	,	,	PUNCT
ijassa-1442	245	15	while	while	SCONJ
ijassa-1442	245	16	fair	fair	ADJ
ijassa-1442	245	17	metrics	metric	NOUN
ijassa-1442	245	18	should	should	AUX
ijassa-1442	245	19	not	not	PART
ijassa-1442	245	20	exceed	exceed	VERB
ijassa-1442	245	21	2	2	NUM
ijassa-1442	245	22	%	%	NOUN
ijassa-1442	245	23	.	.	PUNCT
ijassa-1442	246	1	in	in	ADP
ijassa-1442	246	2	the	the	DET
ijassa-1442	246	3	event	event	NOUN
ijassa-1442	246	4	that	that	PRON
ijassa-1442	246	5	any	any	PRON
ijassa-1442	246	6	of	of	ADP
ijassa-1442	246	7	these	these	DET
ijassa-1442	246	8	requirements	requirement	NOUN
ijassa-1442	246	9	were	be	AUX
ijassa-1442	246	10	not	not	PART
ijassa-1442	246	11	met	meet	VERB
ijassa-1442	246	12	,	,	PUNCT
ijassa-1442	246	13	the	the	DET
ijassa-1442	246	14	model	model	NOUN
ijassa-1442	246	15	was	be	AUX
ijassa-1442	246	16	retrained	retrain	VERB
ijassa-1442	246	17	with	with	ADP
ijassa-1442	246	18	different	different	ADJ
ijassa-1442	246	19	initial	initial	ADJ
ijassa-1442	246	20	weights	weight	NOUN
ijassa-1442	246	21	.	.	PUNCT
ijassa-1442	247	1	5	5	NUM
ijassa-1442	247	2	.	.	X
ijassa-1442	247	3	experiments	experiment	NOUN
ijassa-1442	247	4	in	in	ADP
ijassa-1442	247	5	this	this	DET
ijassa-1442	247	6	section	section	NOUN
ijassa-1442	247	7	we	we	PRON
ijassa-1442	247	8	will	will	AUX
ijassa-1442	247	9	compare	compare	VERB
ijassa-1442	247	10	different	different	ADJ
ijassa-1442	247	11	approaches	approach	NOUN
ijassa-1442	247	12	of	of	ADP
ijassa-1442	247	13	privacy	privacy	NOUN
ijassa-1442	247	14	preservation	preservation	NOUN
ijassa-1442	247	15	and/or	and/or	CCONJ
ijassa-1442	247	16	biasmitigation	biasmitigation	NOUN
ijassa-1442	247	17	strategies	strategy	NOUN
ijassa-1442	247	18	.	.	PUNCT
ijassa-1442	248	1	all	all	DET
ijassa-1442	248	2	models	model	NOUN
ijassa-1442	248	3	with	with	ADP
ijassa-1442	248	4	privacy	privacy	NOUN
ijassa-1442	248	5	preservation	preservation	NOUN
ijassa-1442	248	6	and/or	and/or	CCONJ
ijassa-1442	248	7	bias	bias	NOUN
ijassa-1442	248	8	-	-	PUNCT
ijassa-1442	248	9	mitigation	mitigation	NOUN
ijassa-1442	248	10	was	be	AUX
ijassa-1442	248	11	trained	train	VERB
ijassa-1442	248	12	several	several	ADJ
ijassa-1442	248	13	times	time	NOUN
ijassa-1442	248	14	to	to	PART
ijassa-1442	248	15	calculate	calculate	VERB
ijassa-1442	248	16	mean	mean	NOUN
ijassa-1442	248	17	and	and	CCONJ
ijassa-1442	248	18	standard	standard	ADJ
ijassa-1442	248	19	deviation	deviation	NOUN
ijassa-1442	248	20	of	of	ADP
ijassa-1442	248	21	accuracy	accuracy	NOUN
ijassa-1442	248	22	and	and	CCONJ
ijassa-1442	248	23	fair	fair	ADJ
ijassa-1442	248	24	metrics	metric	NOUN
ijassa-1442	248	25	.	.	PUNCT
ijassa-1442	249	1	this	this	DET
ijassa-1442	249	2	work	work	NOUN
ijassa-1442	249	3	considers	consider	VERB
ijassa-1442	249	4	models	model	NOUN
ijassa-1442	249	5	with	with	ADP
ijassa-1442	249	6	various	various	ADJ
ijassa-1442	249	7	configurations	configuration	NOUN
ijassa-1442	249	8	as	as	SCONJ
ijassa-1442	249	9	described	describe	VERB
ijassa-1442	249	10	in	in	ADP
ijassa-1442	249	11	table	table	NOUN
ijassa-1442	249	12	3	3	NUM
ijassa-1442	249	13	.	.	PUNCT
ijassa-1442	250	1	since	since	SCONJ
ijassa-1442	250	2	each	each	DET
ijassa-1442	250	3	configuration	configuration	NOUN
ijassa-1442	250	4	was	be	AUX
ijassa-1442	250	5	trained	train	VERB
ijassa-1442	250	6	multiple	multiple	ADJ
ijassa-1442	250	7	times	time	NOUN
ijassa-1442	250	8	,	,	PUNCT
ijassa-1442	250	9	in	in	ADP
ijassa-1442	250	10	addition	addition	NOUN
ijassa-1442	250	11	to	to	ADP
ijassa-1442	250	12	the	the	DET
ijassa-1442	250	13	histogram	histogram	NOUN
ijassa-1442	250	14	,	,	PUNCT
ijassa-1442	250	15	a	a	DET
ijassa-1442	250	16	t	t	NOUN
ijassa-1442	250	17	-	-	PUNCT
ijassa-1442	250	18	test	test	NOUN
ijassa-1442	250	19	table	table	NOUN
ijassa-1442	250	20	with	with	ADP
ijassa-1442	250	21	a	a	DET
ijassa-1442	250	22	pvalue	pvalue	NOUN
ijassa-1442	250	23	of	of	ADP
ijassa-1442	250	24	5	5	NUM
ijassa-1442	250	25	was	be	AUX
ijassa-1442	250	26	used	use	VERB
ijassa-1442	250	27	for	for	ADP
ijassa-1442	250	28	comparison	comparison	NOUN
ijassa-1442	250	29	.	.	PUNCT
ijassa-1442	251	1	table	table	NOUN
ijassa-1442	251	2	3	3	NUM
ijassa-1442	251	3	changing	change	VERB
ijassa-1442	251	4	parameters	parameter	NOUN
ijassa-1442	251	5	parameter	parameter	NOUN
ijassa-1442	251	6	values	value	NOUN
ijassa-1442	251	7	dataset	dataset	VERB
ijassa-1442	251	8	adult	adult	NOUN
ijassa-1442	251	9	model	model	NOUN
ijassa-1442	251	10	architecture	architecture	NOUN
ijassa-1442	251	11	laftr	laftr	NOUN
ijassa-1442	251	12	-	-	PUNCT
ijassa-1442	251	13	dp	dp	NOUN
ijassa-1442	251	14	,	,	PUNCT
ijassa-1442	251	15	laftr	laftr	ADJ
ijassa-1442	251	16	-	-	PUNCT
ijassa-1442	251	17	eod	eod	NOUN
ijassa-1442	251	18	adversary	adversary	NOUN
ijassa-1442	251	19	module	module	NOUN
ijassa-1442	251	20	2	2	NUM
ijassa-1442	251	21	layers	layer	NOUN
ijassa-1442	251	22	*	*	PUNCT
ijassa-1442	251	23	32	32	NUM
ijassa-1442	251	24	neurons	neuron	NOUN
ijassa-1442	251	25	;	;	PUNCT
ijassa-1442	251	26	4	4	NUM
ijassa-1442	251	27	layers	layer	NOUN
ijassa-1442	251	28	*	*	SYM
ijassa-1442	251	29	64	64	NUM
ijassa-1442	251	30	neurons	neuron	NOUN
ijassa-1442	251	31	privacy	privacy	NOUN
ijassa-1442	251	32	in	in	ADP
ijassa-1442	251	33	no	no	DET
ijassa-1442	251	34	privacy	privacy	NOUN
ijassa-1442	251	35	;	;	PUNCT
ijassa-1442	251	36	encoder	encoder	NOUN
ijassa-1442	251	37	/	/	SYM
ijassa-1442	251	38	classifier	classifier	NOUN
ijassa-1442	251	39	;	;	PUNCT
ijassa-1442	251	40	encoder	encoder	NOUN
ijassa-1442	251	41	/	/	SYM
ijassa-1442	251	42	classifier	classifier	NOUN
ijassa-1442	251	43	/	/	SYM
ijassa-1442	251	44	adversary	adversary	NOUN
ijassa-1442	251	45	1	1	NUM
ijassa-1442	251	46	,	,	PUNCT
ijassa-1442	251	47	3	3	NUM
ijassa-1442	251	48	,	,	PUNCT
ijassa-1442	251	49	10	10	NUM
ijassa-1442	251	50	,	,	PUNCT
ijassa-1442	251	51	30	30	NUM
ijassa-1442	251	52	to	to	PART
ijassa-1442	251	53	ensure	ensure	VERB
ijassa-1442	251	54	that	that	SCONJ
ijassa-1442	251	55	the	the	DET
ijassa-1442	251	56	results	result	NOUN
ijassa-1442	251	57	were	be	AUX
ijassa-1442	251	58	robust	robust	ADJ
ijassa-1442	251	59	a	a	DET
ijassa-1442	251	60	diverse	diverse	ADJ
ijassa-1442	251	61	set	set	NOUN
ijassa-1442	251	62	of	of	ADP
ijassa-1442	251	63	37	37	NUM
ijassa-1442	251	64	models	model	NOUN
ijassa-1442	251	65	were	be	AUX
ijassa-1442	251	66	trained	train	VERB
ijassa-1442	251	67	for	for	ADP
ijassa-1442	251	68	each	each	DET
ijassa-1442	251	69	dataset	dataset	NOUN
ijassa-1442	251	70	.	.	PUNCT
ijassa-1442	252	1	these	these	DET
ijassa-1442	252	2	models	model	NOUN
ijassa-1442	252	3	varied	varied	ADJ
ijassa-1442	252	4	in	in	ADP
ijassa-1442	252	5	terms	term	NOUN
ijassa-1442	252	6	of	of	ADP
ijassa-1442	252	7	their	their	PRON
ijassa-1442	252	8	architecture	architecture	NOUN
ijassa-1442	252	9	,	,	PUNCT
ijassa-1442	252	10	hyperparameters	hyperparameter	NOUN
ijassa-1442	252	11	,	,	PUNCT
ijassa-1442	252	12	and	and	CCONJ
ijassa-1442	252	13	level	level	NOUN
ijassa-1442	252	14	of	of	ADP
ijassa-1442	252	15	privacy	privacy	NOUN
ijassa-1442	252	16	.	.	PUNCT
ijassa-1442	253	1	this	this	DET
ijassa-1442	253	2	approach	approach	NOUN
ijassa-1442	253	3	allowed	allow	VERB
ijassa-1442	253	4	for	for	ADP
ijassa-1442	253	5	a	a	DET
ijassa-1442	253	6	comprehensive	comprehensive	ADJ
ijassa-1442	253	7	evaluation	evaluation	NOUN
ijassa-1442	253	8	of	of	ADP
ijassa-1442	253	9	the	the	DET
ijassa-1442	253	10	performance	performance	NOUN
ijassa-1442	253	11	of	of	ADP
ijassa-1442	253	12	the	the	DET
ijassa-1442	253	13	models	model	NOUN
ijassa-1442	253	14	under	under	ADP
ijassa-1442	253	15	different	different	ADJ
ijassa-1442	253	16	configurations	configuration	NOUN
ijassa-1442	253	17	and	and	CCONJ
ijassa-1442	253	18	helped	help	VERB
ijassa-1442	253	19	to	to	PART
ijassa-1442	253	20	identify	identify	VERB
ijassa-1442	253	21	the	the	DET
ijassa-1442	253	22	most	most	ADV
ijassa-1442	253	23	effective	effective	ADJ
ijassa-1442	253	24	configurations	configuration	NOUN
ijassa-1442	253	25	for	for	ADP
ijassa-1442	253	26	each	each	DET
ijassa-1442	253	27	dataset	dataset	NOUN
ijassa-1442	253	28	.	.	PUNCT
ijassa-1442	254	1	a	a	DET
ijassa-1442	254	2	t	t	NOUN
ijassa-1442	254	3	-	-	PUNCT
ijassa-1442	254	4	test	test	NOUN
ijassa-1442	254	5	will	will	AUX
ijassa-1442	254	6	be	be	AUX
ijassa-1442	254	7	utilized	utilize	VERB
ijassa-1442	254	8	to	to	PART
ijassa-1442	254	9	compare	compare	VERB
ijassa-1442	254	10	the	the	DET
ijassa-1442	254	11	performance	performance	NOUN
ijassa-1442	254	12	of	of	ADP
ijassa-1442	254	13	models	model	NOUN
ijassa-1442	254	14	.	.	PUNCT
ijassa-1442	255	1	t	t	X
ijassa-1442	255	2	-	-	PUNCT
ijassa-1442	255	3	test	test	NOUN
ijassa-1442	255	4	a	a	DET
ijassa-1442	255	5	statistical	statistical	ADJ
ijassa-1442	255	6	hypothesis	hypothesis	NOUN
ijassa-1442	255	7	test	test	NOUN
ijassa-1442	255	8	that	that	PRON
ijassa-1442	255	9	is	be	AUX
ijassa-1442	255	10	used	use	VERB
ijassa-1442	255	11	to	to	PART
ijassa-1442	255	12	determine	determine	VERB
ijassa-1442	255	13	if	if	SCONJ
ijassa-1442	255	14	there	there	PRON
ijassa-1442	255	15	is	be	VERB
ijassa-1442	255	16	a	a	DET
ijassa-1442	255	17	significant	significant	ADJ
ijassa-1442	255	18	difference	difference	NOUN
ijassa-1442	255	19	between	between	ADP
ijassa-1442	255	20	the	the	DET
ijassa-1442	255	21	means	mean	NOUN
ijassa-1442	255	22	of	of	ADP
ijassa-1442	255	23	two	two	NUM
ijassa-1442	255	24	groups	group	NOUN
ijassa-1442	255	25	.	.	PUNCT
ijassa-1442	256	1	in	in	ADP
ijassa-1442	256	2	the	the	DET
ijassa-1442	256	3	context	context	NOUN
ijassa-1442	256	4	of	of	ADP
ijassa-1442	256	5	metrics	metric	NOUN
ijassa-1442	256	6	,	,	PUNCT
ijassa-1442	256	7	t	t	NOUN
ijassa-1442	256	8	-	-	PUNCT
ijassa-1442	256	9	tests	test	NOUN
ijassa-1442	256	10	can	can	AUX
ijassa-1442	256	11	be	be	AUX
ijassa-1442	256	12	used	use	VERB
ijassa-1442	256	13	to	to	PART
ijassa-1442	256	14	determine	determine	VERB
ijassa-1442	256	15	if	if	SCONJ
ijassa-1442	256	16	there	there	PRON
ijassa-1442	256	17	is	be	VERB
ijassa-1442	256	18	a	a	DET
ijassa-1442	256	19	statistically	statistically	ADV
ijassa-1442	256	20	significant	significant	ADJ
ijassa-1442	256	21	difference	difference	NOUN
ijassa-1442	256	22	in	in	ADP
ijassa-1442	256	23	the	the	DET
ijassa-1442	256	24	performance	performance	NOUN
ijassa-1442	256	25	of	of	ADP
ijassa-1442	256	26	two	two	NUM
ijassa-1442	256	27	models	model	NOUN
ijassa-1442	256	28	,	,	PUNCT
ijassa-1442	256	29	or	or	CCONJ
ijassa-1442	256	30	if	if	SCONJ
ijassa-1442	256	31	a	a	DET
ijassa-1442	256	32	certain	certain	ADJ
ijassa-1442	256	33	modification	modification	NOUN
ijassa-1442	256	34	or	or	CCONJ
ijassa-1442	256	35	intervention	intervention	NOUN
ijassa-1442	256	36	has	have	AUX
ijassa-1442	256	37	had	have	VERB
ijassa-1442	256	38	a	a	DET
ijassa-1442	256	39	significant	significant	ADJ
ijassa-1442	256	40	effect	effect	NOUN
ijassa-1442	256	41	on	on	ADP
ijassa-1442	256	42	the	the	DET
ijassa-1442	256	43	performance	performance	NOUN
ijassa-1442	256	44	of	of	ADP
ijassa-1442	256	45	a	a	DET
ijassa-1442	256	46	model	model	NOUN
ijassa-1442	256	47	.	.	PUNCT
ijassa-1442	257	1	by	by	ADP
ijassa-1442	257	2	using	use	VERB
ijassa-1442	257	3	t	t	NOUN
ijassa-1442	257	4	-	-	PUNCT
ijassa-1442	257	5	tests	test	NOUN
ijassa-1442	257	6	,	,	PUNCT
ijassa-1442	257	7	we	we	PRON
ijassa-1442	257	8	can	can	AUX
ijassa-1442	257	9	make	make	VERB
ijassa-1442	257	10	informed	informed	ADJ
ijassa-1442	257	11	decisions	decision	NOUN
ijassa-1442	257	12	about	about	ADP
ijassa-1442	257	13	the	the	DET
ijassa-1442	257	14	effectiveness	effectiveness	NOUN
ijassa-1442	257	15	of	of	ADP
ijassa-1442	257	16	different	different	ADJ
ijassa-1442	257	17	strategies	strategy	NOUN
ijassa-1442	257	18	for	for	ADP
ijassa-1442	257	19	improving	improve	VERB
ijassa-1442	257	20	the	the	DET
ijassa-1442	257	21	performance	performance	NOUN
ijassa-1442	257	22	or	or	CCONJ
ijassa-1442	257	23	fairness	fairness	NOUN
ijassa-1442	257	24	of	of	ADP
ijassa-1442	257	25	machine	machine	NOUN
ijassa-1442	257	26	learning	learning	NOUN
ijassa-1442	257	27	models	model	NOUN
ijassa-1442	257	28	.	.	PUNCT
ijassa-1442	258	1	there	there	PRON
ijassa-1442	258	2	are	be	VERB
ijassa-1442	258	3	several	several	ADJ
ijassa-1442	258	4	conventions	convention	NOUN
ijassa-1442	258	5	in	in	ADP
ijassa-1442	258	6	the	the	DET
ijassa-1442	258	7	model	model	NOUN
ijassa-1442	258	8	names	name	NOUN
ijassa-1442	258	9	.	.	PUNCT
ijassa-1442	259	1	“	"	PUNCT
ijassa-1442	259	2	unfair|no	unfair|no	PROPN
ijassa-1442	259	3	privacy	privacy	NOUN
ijassa-1442	259	4	”	"	PUNCT
ijassa-1442	259	5	logistic	logistic	ADJ
ijassa-1442	259	6	regression	regression	NOUN
ijassa-1442	259	7	learned	learn	VERB
ijassa-1442	259	8	on	on	ADP
ijassa-1442	259	9	raw	raw	ADJ
ijassa-1442	259	10	data	datum	NOUN
ijassa-1442	259	11	without	without	ADP
ijassa-1442	259	12	any	any	DET
ijassa-1442	259	13	modifications	modification	NOUN
ijassa-1442	259	14	.	.	PUNCT
ijassa-1442	260	1	“	"	PUNCT
ijassa-1442	260	2	adversary	adversary	NOUN
ijassa-1442	260	3	=	=	SYM
ijassa-1442	260	4	classifier	classifier	NOUN
ijassa-1442	260	5	”	"	PUNCT
ijassa-1442	260	6	means	mean	VERB
ijassa-1442	260	7	that	that	SCONJ
ijassa-1442	260	8	modules	module	NOUN
ijassa-1442	260	9	of	of	ADP
ijassa-1442	260	10	laftr	laftr	NOUN
ijassa-1442	260	11	have	have	VERB
ijassa-1442	260	12	the	the	DET
ijassa-1442	260	13	same	same	ADJ
ijassa-1442	260	14	structure	structure	NOUN
ijassa-1442	260	15	,	,	PUNCT
ijassa-1442	260	16	“	"	PUNCT
ijassa-1442	260	17	adversary	adversary	NOUN
ijassa-1442	260	18	>	>	X
ijassa-1442	260	19	classifier	classifier	NOUN
ijassa-1442	260	20	”	"	PUNCT
ijassa-1442	260	21	means	mean	VERB
ijassa-1442	260	22	that	that	SCONJ
ijassa-1442	260	23	adversary	adversary	NOUN
ijassa-1442	260	24	part	part	NOUN
ijassa-1442	260	25	stronger	strong	ADJ
ijassa-1442	260	26	(	(	PUNCT
ijassa-1442	260	27	2	2	NUM
ijassa-1442	260	28	times	time	NOUN
ijassa-1442	260	29	more	more	ADJ
ijassa-1442	260	30	layers	layer	NOUN
ijassa-1442	260	31	and	and	CCONJ
ijassa-1442	260	32	2	2	NUM
ijassa-1442	260	33	times	time	NOUN
ijassa-1442	260	34	more	more	ADJ
ijassa-1442	260	35	neurons	neuron	NOUN
ijassa-1442	260	36	in	in	ADP
ijassa-1442	260	37	each	each	DET
ijassa-1442	260	38	layer	layer	NOUN
ijassa-1442	260	39	)	)	PUNCT
ijassa-1442	260	40	.	.	PUNCT
ijassa-1442	261	1	5.1	5.1	NUM
ijassa-1442	261	2	.	.	PUNCT
ijassa-1442	261	3	adult	adult	NOUN
ijassa-1442	261	4	dataset	dataset	VERB
ijassa-1442	261	5	the	the	DET
ijassa-1442	261	6	adult	adult	NOUN
ijassa-1442	261	7	dataset	dataset	NOUN
ijassa-1442	261	8	is	be	AUX
ijassa-1442	261	9	a	a	DET
ijassa-1442	261	10	well	well	ADV
ijassa-1442	261	11	-	-	PUNCT
ijassa-1442	261	12	known	know	VERB
ijassa-1442	261	13	benchmark	benchmark	NOUN
ijassa-1442	261	14	dataset	dataset	NOUN
ijassa-1442	261	15	in	in	ADP
ijassa-1442	261	16	machine	machine	NOUN
ijassa-1442	261	17	learning	learning	NOUN
ijassa-1442	261	18	that	that	PRON
ijassa-1442	261	19	contains	contain	VERB
ijassa-1442	261	20	demographic	demographic	ADJ
ijassa-1442	261	21	and	and	CCONJ
ijassa-1442	261	22	employment	employment	NOUN
ijassa-1442	261	23	-	-	PUNCT
ijassa-1442	261	24	related	relate	VERB
ijassa-1442	261	25	information	information	NOUN
ijassa-1442	261	26	of	of	ADP
ijassa-1442	261	27	individuals	individual	NOUN
ijassa-1442	261	28	to	to	PART
ijassa-1442	261	29	predict	predict	VERB
ijassa-1442	261	30	whether	whether	SCONJ
ijassa-1442	261	31	their	their	PRON
ijassa-1442	261	32	income	income	NOUN
ijassa-1442	261	33	is	be	AUX
ijassa-1442	261	34	above	above	ADP
ijassa-1442	261	35	or	or	CCONJ
ijassa-1442	261	36	below	below	ADP
ijassa-1442	261	37	a	a	DET
ijassa-1442	261	38	certain	certain	ADJ
ijassa-1442	261	39	threshold	threshold	NOUN
ijassa-1442	261	40	.	.	PUNCT
ijassa-1442	262	1	in	in	ADP
ijassa-1442	262	2	this	this	DET
ijassa-1442	262	3	case	case	NOUN
ijassa-1442	262	4	each	each	DET
ijassa-1442	262	5	configuration	configuration	NOUN
ijassa-1442	262	6	of	of	ADP
ijassa-1442	262	7	models	model	NOUN
ijassa-1442	262	8	was	be	AUX
ijassa-1442	262	9	trained	train	VERB
ijassa-1442	262	10	10	10	NUM
ijassa-1442	262	11	times	time	NOUN
ijassa-1442	262	12	.	.	PUNCT
ijassa-1442	263	1	number	number	NOUN
ijassa-1442	263	2	of	of	ADP
ijassa-1442	263	3	epochs	epoch	NOUN
ijassa-1442	263	4	for	for	ADP
ijassa-1442	263	5	each	each	DET
ijassa-1442	263	6	training	training	NOUN
ijassa-1442	263	7	was	be	AUX
ijassa-1442	263	8	set	set	VERB
ijassa-1442	263	9	to	to	ADP
ijassa-1442	263	10	250	250	NUM
ijassa-1442	263	11	.	.	PUNCT
ijassa-1442	264	1	in	in	ADP
ijassa-1442	264	2	all	all	DET
ijassa-1442	264	3	next	next	ADJ
ijassa-1442	264	4	datasets	dataset	NOUN
ijassa-1442	264	5	,	,	PUNCT
ijassa-1442	264	6	based	base	VERB
ijassa-1442	264	7	on	on	ADP
ijassa-1442	264	8	t	t	PROPN
ijassa-1442	264	9	-	-	PUNCT
ijassa-1442	264	10	test	test	NOUN
ijassa-1442	264	11	,	,	PUNCT
ijassa-1442	264	12	protected	protect	VERB
ijassa-1442	264	13	models	model	NOUN
ijassa-1442	264	14	demonstrated	demonstrate	VERB
ijassa-1442	264	15	similar	similar	ADJ
ijassa-1442	264	16	performance	performance	NOUN
ijassa-1442	264	17	across	across	ADP
ijassa-1442	264	18	different	different	ADJ
ijassa-1442	264	19	levels	level	NOUN
ijassa-1442	264	20	of	of	ADP
ijassa-1442	264	21	50	50	NUM
ijassa-1442	264	22	a.	a.	NOUN
ijassa-1442	264	23	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	264	24	,	,	PUNCT
ijassa-1442	264	25	r.	r.	PROPN
ijassa-1442	264	26	sabitov	sabitov	PROPN
ijassa-1442	264	27	,	,	PUNCT
ijassa-1442	264	28	g.	g.	PROPN
ijassa-1442	264	29	smirnova	smirnova	PROPN
ijassa-1442	264	30	,	,	PUNCT
ijassa-1442	264	31	sh	sh	PROPN
ijassa-1442	264	32	.	.	PUNCT
ijassa-1442	264	33	sabitov	sabitov	PROPN
ijassa-1442	264	34	copyright	copyright	NOUN
ijassa-1442	265	1	©	©	PROPN
ijassa-1442	265	2	2023	2023	NUM
ijassa-1442	265	3	assa	assa	PROPN
ijassa-1442	265	4	adv	adv	PROPN
ijassa-1442	265	5	.	.	PUNCT
ijassa-1442	266	1	in	in	ADP
ijassa-1442	266	2	systems	system	NOUN
ijassa-1442	266	3	science	science	NOUN
ijassa-1442	266	4	and	and	CCONJ
ijassa-1442	266	5	appl	appl	NOUN
ijassa-1442	266	6	.	.	PUNCT
ijassa-1442	267	1	(	(	PUNCT
ijassa-1442	267	2	2023	2023	NUM
ijassa-1442	267	3	)	)	PUNCT
ijassa-1442	267	4	privacy	privacy	NOUN
ijassa-1442	267	5	,	,	PUNCT
ijassa-1442	267	6	regardless	regardless	ADV
ijassa-1442	267	7	of	of	ADP
ijassa-1442	267	8	the	the	DET
ijassa-1442	267	9	level	level	NOUN
ijassa-1442	267	10	of	of	ADP
ijassa-1442	267	11	noise	noise	NOUN
ijassa-1442	267	12	in	in	ADP
ijassa-1442	267	13	the	the	DET
ijassa-1442	267	14	gradients	gradient	NOUN
ijassa-1442	267	15	during	during	ADP
ijassa-1442	267	16	training	training	NOUN
ijassa-1442	267	17	and	and	CCONJ
ijassa-1442	267	18	the	the	DET
ijassa-1442	267	19	neural	neural	ADJ
ijassa-1442	267	20	network	network	NOUN
ijassa-1442	267	21	modules	module	NOUN
ijassa-1442	267	22	in	in	ADP
ijassa-1442	267	23	which	which	PRON
ijassa-1442	267	24	this	this	DET
ijassa-1442	267	25	noise	noise	NOUN
ijassa-1442	267	26	was	be	AUX
ijassa-1442	267	27	injected	inject	VERB
ijassa-1442	267	28	.	.	PUNCT
ijassa-1442	268	1	therefore	therefore	ADV
ijassa-1442	268	2	,	,	PUNCT
ijassa-1442	268	3	we	we	PRON
ijassa-1442	268	4	will	will	AUX
ijassa-1442	268	5	consolidate	consolidate	VERB
ijassa-1442	268	6	the	the	DET
ijassa-1442	268	7	results	result	NOUN
ijassa-1442	268	8	with	with	ADP
ijassa-1442	268	9	different	different	ADJ
ijassa-1442	268	10	epsilon	epsilon	PROPN
ijassa-1442	268	11	values	value	NOUN
ijassa-1442	268	12	and	and	CCONJ
ijassa-1442	268	13	different	different	ADJ
ijassa-1442	268	14	privacy	privacy	NOUN
ijassa-1442	268	15	injection	injection	NOUN
ijassa-1442	268	16	configurations	configuration	NOUN
ijassa-1442	268	17	.	.	PUNCT
ijassa-1442	269	1	next	next	ADV
ijassa-1442	269	2	,	,	PUNCT
ijassa-1442	269	3	tables	table	NOUN
ijassa-1442	269	4	will	will	AUX
ijassa-1442	269	5	be	be	AUX
ijassa-1442	269	6	presented	present	VERB
ijassa-1442	269	7	for	for	ADP
ijassa-1442	269	8	each	each	DET
ijassa-1442	269	9	metric	metric	NOUN
ijassa-1442	269	10	,	,	PUNCT
ijassa-1442	269	11	comparing	compare	VERB
ijassa-1442	269	12	the	the	DET
ijassa-1442	269	13	minimum	minimum	ADJ
ijassa-1442	269	14	,	,	PUNCT
ijassa-1442	269	15	maximum	maximum	ADJ
ijassa-1442	269	16	,	,	PUNCT
ijassa-1442	269	17	and	and	CCONJ
ijassa-1442	269	18	average	average	ADJ
ijassa-1442	269	19	values	value	NOUN
ijassa-1442	269	20	among	among	ADP
ijassa-1442	269	21	all	all	DET
ijassa-1442	269	22	implementations	implementation	NOUN
ijassa-1442	269	23	.	.	PUNCT
ijassa-1442	270	1	the	the	DET
ijassa-1442	270	2	results	result	NOUN
ijassa-1442	270	3	will	will	AUX
ijassa-1442	270	4	be	be	AUX
ijassa-1442	270	5	grouped	group	VERB
ijassa-1442	270	6	by	by	ADP
ijassa-1442	270	7	model	model	NOUN
ijassa-1442	270	8	type	type	NOUN
ijassa-1442	270	9	and	and	CCONJ
ijassa-1442	270	10	adversary	adversary	NOUN
ijassa-1442	270	11	strength	strength	NOUN
ijassa-1442	270	12	,	,	PUNCT
ijassa-1442	270	13	taking	take	VERB
ijassa-1442	270	14	into	into	ADP
ijassa-1442	270	15	account	account	NOUN
ijassa-1442	270	16	the	the	DET
ijassa-1442	270	17	conditions	condition	NOUN
ijassa-1442	270	18	described	describe	VERB
ijassa-1442	270	19	above	above	ADV
ijassa-1442	270	20	.	.	PUNCT
ijassa-1442	271	1	5.2	5.2	NUM
ijassa-1442	271	2	.	.	PUNCT
ijassa-1442	271	3	difference	difference	NOUN
ijassa-1442	271	4	of	of	ADP
ijassa-1442	271	5	demographic	demographic	ADJ
ijassa-1442	271	6	parity	parity	NOUN
ijassa-1442	271	7	there	there	PRON
ijassa-1442	271	8	are	be	VERB
ijassa-1442	271	9	results	result	NOUN
ijassa-1442	271	10	of	of	ADP
ijassa-1442	271	11	measuring	measure	VERB
ijassa-1442	271	12	first	first	ADJ
ijassa-1442	271	13	fair	fair	ADJ
ijassa-1442	271	14	metric	metric	ADJ
ijassa-1442	271	15	difference	difference	NOUN
ijassa-1442	271	16	of	of	ADP
ijassa-1442	271	17	demographic	demographic	ADJ
ijassa-1442	271	18	parity	parity	NOUN
ijassa-1442	271	19	–	–	PUNCT
ijassa-1442	271	20	.	.	PUNCT
ijassa-1442	272	1	based	base	VERB
ijassa-1442	272	2	on	on	ADP
ijassa-1442	272	3	the	the	DET
ijassa-1442	272	4	fig	fig	NOUN
ijassa-1442	272	5	.	.	PUNCT
ijassa-1442	273	1	2	2	NUM
ijassa-1442	273	2	,	,	PUNCT
ijassa-1442	273	3	the	the	DET
ijassa-1442	273	4	comparison	comparison	NOUN
ijassa-1442	273	5	models	model	NOUN
ijassa-1442	273	6	with	with	ADP
ijassa-1442	273	7	different	different	ADJ
ijassa-1442	273	8	privacy	privacy	NOUN
ijassa-1442	273	9	levels	level	NOUN
ijassa-1442	273	10	,	,	PUNCT
ijassa-1442	273	11	epsilon	epsilon	PROPN
ijassa-1442	273	12	values	value	NOUN
ijassa-1442	273	13	,	,	PUNCT
ijassa-1442	273	14	and	and	CCONJ
ijassa-1442	273	15	adversary	adversary	NOUN
ijassa-1442	273	16	-	-	PUNCT
ijassa-1442	273	17	classifier	classifier	NOUN
ijassa-1442	273	18	strengths	strength	NOUN
ijassa-1442	273	19	we	we	PRON
ijassa-1442	273	20	can	can	AUX
ijassa-1442	273	21	say	say	VERB
ijassa-1442	273	22	for	for	ADP
ijassa-1442	273	23	sure	sure	ADJ
ijassa-1442	273	24	that	that	SCONJ
ijassa-1442	273	25	the	the	DET
ijassa-1442	273	26	"	"	PUNCT
ijassa-1442	273	27	unfair|no	unfair|no	PROPN
ijassa-1442	273	28	privacy	privacy	NOUN
ijassa-1442	273	29	"	"	PUNCT
ijassa-1442	273	30	model	model	NOUN
ijassa-1442	273	31	is	be	AUX
ijassa-1442	273	32	the	the	DET
ijassa-1442	273	33	most	most	ADV
ijassa-1442	273	34	unfair	unfair	ADJ
ijassa-1442	273	35	.	.	PUNCT
ijassa-1442	274	1	fig	fig	NOUN
ijassa-1442	274	2	.	.	PUNCT
ijassa-1442	275	1	2	2	X
ijassa-1442	275	2	.	.	X
ijassa-1442	275	3	dependence	dependence	NOUN
ijassa-1442	275	4	of	of	ADP
ijassa-1442	275	5	on	on	ADP
ijassa-1442	275	6	for	for	ADP
ijassa-1442	275	7	adult	adult	NOUN
ijassa-1442	275	8	dataset	dataset	NOUN
ijassa-1442	275	9	as	as	SCONJ
ijassa-1442	275	10	observed	observe	VERB
ijassa-1442	275	11	in	in	ADP
ijassa-1442	275	12	table	table	NOUN
ijassa-1442	275	13	4	4	NUM
ijassa-1442	275	14	,	,	PUNCT
ijassa-1442	275	15	for	for	ADP
ijassa-1442	275	16	laftr	laftr	ADJ
ijassa-1442	275	17	-	-	PUNCT
ijassa-1442	275	18	dp	dp	NOUN
ijassa-1442	275	19	,	,	PUNCT
ijassa-1442	275	20	both	both	CCONJ
ijassa-1442	275	21	the	the	DET
ijassa-1442	275	22	minimum	minimum	ADJ
ijassa-1442	275	23	and	and	CCONJ
ijassa-1442	275	24	average	average	ADJ
ijassa-1442	275	25	values	value	NOUN
ijassa-1442	275	26	of	of	ADP
ijassa-1442	275	27	are	be	AUX
ijassa-1442	275	28	very	very	ADV
ijassa-1442	275	29	low	low	ADJ
ijassa-1442	275	30	,	,	PUNCT
ijassa-1442	275	31	regardless	regardless	ADV
ijassa-1442	275	32	of	of	ADP
ijassa-1442	275	33	the	the	DET
ijassa-1442	275	34	strength	strength	NOUN
ijassa-1442	275	35	of	of	ADP
ijassa-1442	275	36	the	the	DET
ijassa-1442	275	37	adversary	adversary	NOUN
ijassa-1442	275	38	.	.	PUNCT
ijassa-1442	276	1	however	however	ADV
ijassa-1442	276	2	,	,	PUNCT
ijassa-1442	276	3	for	for	ADP
ijassa-1442	276	4	the	the	DET
ijassa-1442	276	5	private	private	ADJ
ijassa-1442	276	6	models	model	NOUN
ijassa-1442	276	7	,	,	PUNCT
ijassa-1442	276	8	balancing	balance	VERB
ijassa-1442	276	9	accuracy	accuracy	NOUN
ijassa-1442	276	10	,	,	PUNCT
ijassa-1442	276	11	fairness	fairness	NOUN
ijassa-1442	276	12	and	and	CCONJ
ijassa-1442	276	13	privacy	privacy	NOUN
ijassa-1442	276	14	in	in	ADP
ijassa-1442	276	15	machine	machine	NOUN
ijassa-1442	276	16	learning	learning	NOUN
ijassa-1442	276	17	…	…	PUNCT
ijassa-1442	276	18	51	51	NUM
ijassa-1442	276	19	copyright	copyright	NOUN
ijassa-1442	276	20	©	©	PROPN
ijassa-1442	276	21	2023	2023	NUM
ijassa-1442	276	22	assa	assa	NOUN
ijassa-1442	276	23	.	.	PUNCT
ijassa-1442	277	1	adv	adv	PROPN
ijassa-1442	277	2	.	.	PUNCT
ijassa-1442	278	1	in	in	ADP
ijassa-1442	278	2	systems	system	NOUN
ijassa-1442	278	3	science	science	NOUN
ijassa-1442	278	4	and	and	CCONJ
ijassa-1442	278	5	appl	appl	NOUN
ijassa-1442	278	6	.	.	PUNCT
ijassa-1442	279	1	(	(	PUNCT
ijassa-1442	279	2	2023	2023	NUM
ijassa-1442	279	3	)	)	PUNCT
ijassa-1442	279	4	the	the	DET
ijassa-1442	279	5	minimum	minimum	ADJ
ijassa-1442	279	6	values	value	NOUN
ijassa-1442	279	7	are	be	AUX
ijassa-1442	279	8	nearly	nearly	ADV
ijassa-1442	279	9	zero	zero	NUM
ijassa-1442	279	10	,	,	PUNCT
ijassa-1442	279	11	while	while	SCONJ
ijassa-1442	279	12	for	for	ADP
ijassa-1442	279	13	the	the	DET
ijassa-1442	279	14	unprotected	unprotected	ADJ
ijassa-1442	279	15	models	model	NOUN
ijassa-1442	279	16	,	,	PUNCT
ijassa-1442	279	17	they	they	PRON
ijassa-1442	279	18	range	range	VERB
ijassa-1442	279	19	from	from	ADP
ijassa-1442	279	20	6	6	NUM
ijassa-1442	279	21	%	%	NOUN
ijassa-1442	279	22	to	to	PART
ijassa-1442	279	23	9	9	NUM
ijassa-1442	279	24	%	%	NOUN
ijassa-1442	279	25	.	.	PUNCT
ijassa-1442	280	1	additionally	additionally	ADV
ijassa-1442	280	2	,	,	PUNCT
ijassa-1442	280	3	in	in	ADP
ijassa-1442	280	4	the	the	DET
ijassa-1442	280	5	case	case	NOUN
ijassa-1442	280	6	of	of	ADP
ijassa-1442	280	7	protected	protect	VERB
ijassa-1442	280	8	models	model	NOUN
ijassa-1442	280	9	,	,	PUNCT
ijassa-1442	280	10	the	the	DET
ijassa-1442	280	11	average	average	ADJ
ijassa-1442	280	12	value	value	NOUN
ijassa-1442	280	13	is	be	AUX
ijassa-1442	280	14	independent	independent	ADJ
ijassa-1442	280	15	of	of	ADP
ijassa-1442	280	16	the	the	DET
ijassa-1442	280	17	adversary	adversary	NOUN
ijassa-1442	280	18	's	's	PART
ijassa-1442	280	19	strength	strength	NOUN
ijassa-1442	280	20	,	,	PUNCT
ijassa-1442	280	21	with	with	ADP
ijassa-1442	280	22	a	a	DET
ijassa-1442	280	23	difference	difference	NOUN
ijassa-1442	280	24	of	of	ADP
ijassa-1442	280	25	only	only	ADV
ijassa-1442	280	26	3	3	NUM
ijassa-1442	280	27	%	%	NOUN
ijassa-1442	280	28	.	.	PUNCT
ijassa-1442	281	1	the	the	DET
ijassa-1442	281	2	maximum	maximum	ADJ
ijassa-1442	281	3	value	value	NOUN
ijassa-1442	281	4	does	do	AUX
ijassa-1442	281	5	not	not	PART
ijassa-1442	281	6	exceed	exceed	VERB
ijassa-1442	281	7	that	that	PRON
ijassa-1442	281	8	of	of	ADP
ijassa-1442	281	9	the	the	DET
ijassa-1442	281	10	unfair	unfair	ADJ
ijassa-1442	281	11	approach	approach	NOUN
ijassa-1442	281	12	in	in	ADP
ijassa-1442	281	13	any	any	DET
ijassa-1442	281	14	case	case	NOUN
ijassa-1442	281	15	,	,	PUNCT
ijassa-1442	281	16	but	but	CCONJ
ijassa-1442	281	17	the	the	DET
ijassa-1442	281	18	difference	difference	NOUN
ijassa-1442	281	19	ranges	range	VERB
ijassa-1442	281	20	from	from	ADP
ijassa-1442	281	21	0.6	0.6	NUM
ijassa-1442	281	22	%	%	NOUN
ijassa-1442	281	23	to	to	PART
ijassa-1442	281	24	7	7	NUM
ijassa-1442	281	25	%	%	NOUN
ijassa-1442	281	26	.	.	PUNCT
ijassa-1442	282	1	regarding	regard	VERB
ijassa-1442	282	2	laftr	laftr	ADJ
ijassa-1442	282	3	-	-	PUNCT
ijassa-1442	282	4	eod	eod	NOUN
ijassa-1442	282	5	,	,	PUNCT
ijassa-1442	282	6	the	the	DET
ijassa-1442	282	7	behavior	behavior	NOUN
ijassa-1442	282	8	of	of	ADP
ijassa-1442	282	9	the	the	DET
ijassa-1442	282	10	results	result	NOUN
ijassa-1442	282	11	is	be	AUX
ijassa-1442	282	12	comparable	comparable	ADJ
ijassa-1442	282	13	to	to	ADP
ijassa-1442	282	14	laftr	laftr	NOUN
ijassa-1442	282	15	-	-	PUNCT
ijassa-1442	282	16	dp	dp	NOUN
ijassa-1442	282	17	,	,	PUNCT
ijassa-1442	282	18	but	but	CCONJ
ijassa-1442	282	19	with	with	ADP
ijassa-1442	282	20	slight	slight	ADJ
ijassa-1442	282	21	variations	variation	NOUN
ijassa-1442	282	22	and	and	CCONJ
ijassa-1442	282	23	more	more	ADJ
ijassa-1442	282	24	stability	stability	NOUN
ijassa-1442	282	25	in	in	ADP
ijassa-1442	282	26	the	the	DET
ijassa-1442	282	27	values	value	NOUN
ijassa-1442	282	28	.	.	PUNCT
ijassa-1442	283	1	the	the	DET
ijassa-1442	283	2	maximum	maximum	ADJ
ijassa-1442	283	3	difference	difference	NOUN
ijassa-1442	283	4	between	between	ADP
ijassa-1442	283	5	laftr	laftr	NOUN
ijassa-1442	283	6	-	-	PUNCT
ijassa-1442	283	7	eod	eod	NOUN
ijassa-1442	283	8	and	and	CCONJ
ijassa-1442	283	9	the	the	DET
ijassa-1442	283	10	unfair	unfair	ADJ
ijassa-1442	283	11	model	model	NOUN
ijassa-1442	283	12	ranges	range	VERB
ijassa-1442	283	13	from	from	ADP
ijassa-1442	283	14	3.5	3.5	NUM
ijassa-1442	283	15	%	%	NOUN
ijassa-1442	283	16	to	to	ADP
ijassa-1442	283	17	2.5	2.5	NUM
ijassa-1442	283	18	%	%	NOUN
ijassa-1442	283	19	.	.	PUNCT
ijassa-1442	284	1	on	on	ADP
ijassa-1442	284	2	average	average	ADJ
ijassa-1442	284	3	,	,	PUNCT
ijassa-1442	284	4	the	the	DET
ijassa-1442	284	5	minimum	minimum	ADJ
ijassa-1442	284	6	values	value	NOUN
ijassa-1442	284	7	are	be	AUX
ijassa-1442	284	8	slightly	slightly	ADV
ijassa-1442	284	9	lower	low	ADJ
ijassa-1442	284	10	for	for	ADP
ijassa-1442	284	11	this	this	DET
ijassa-1442	284	12	architecture	architecture	NOUN
ijassa-1442	284	13	.	.	PUNCT
ijassa-1442	285	1	in	in	ADP
ijassa-1442	285	2	the	the	DET
ijassa-1442	285	3	absence	absence	NOUN
ijassa-1442	285	4	of	of	ADP
ijassa-1442	285	5	protection	protection	NOUN
ijassa-1442	285	6	,	,	PUNCT
ijassa-1442	285	7	the	the	DET
ijassa-1442	285	8	difference	difference	NOUN
ijassa-1442	285	9	can	can	AUX
ijassa-1442	285	10	reach	reach	VERB
ijassa-1442	285	11	up	up	ADP
ijassa-1442	285	12	to	to	PART
ijassa-1442	285	13	5	5	NUM
ijassa-1442	285	14	%	%	NOUN
ijassa-1442	285	15	in	in	ADP
ijassa-1442	285	16	the	the	DET
ijassa-1442	285	17	case	case	NOUN
ijassa-1442	285	18	of	of	ADP
ijassa-1442	285	19	a	a	DET
ijassa-1442	285	20	weak	weak	ADJ
ijassa-1442	285	21	adversary	adversary	NOUN
ijassa-1442	285	22	.	.	PUNCT
ijassa-1442	286	1	additionally	additionally	ADV
ijassa-1442	286	2	,	,	PUNCT
ijassa-1442	286	3	the	the	DET
ijassa-1442	286	4	strength	strength	NOUN
ijassa-1442	286	5	of	of	ADP
ijassa-1442	286	6	the	the	DET
ijassa-1442	286	7	adversary	adversary	NOUN
ijassa-1442	286	8	has	have	VERB
ijassa-1442	286	9	a	a	DET
ijassa-1442	286	10	stronger	strong	ADJ
ijassa-1442	286	11	impact	impact	NOUN
ijassa-1442	286	12	on	on	ADP
ijassa-1442	286	13	the	the	DET
ijassa-1442	286	14	average	average	ADJ
ijassa-1442	286	15	value	value	NOUN
ijassa-1442	286	16	for	for	ADP
ijassa-1442	286	17	the	the	DET
ijassa-1442	286	18	protected	protect	VERB
ijassa-1442	286	19	models	model	NOUN
ijassa-1442	286	20	compared	compare	VERB
ijassa-1442	286	21	to	to	ADP
ijassa-1442	286	22	the	the	DET
ijassa-1442	286	23	unprotected	unprotected	ADJ
ijassa-1442	286	24	ones	one	NOUN
ijassa-1442	286	25	.	.	PUNCT
ijassa-1442	287	1	table	table	NOUN
ijassa-1442	287	2	4	4	NUM
ijassa-1442	287	3	comparison	comparison	NOUN
ijassa-1442	287	4	.	.	PUNCT
ijassa-1442	288	1	adult	adult	NOUN
ijassa-1442	288	2	dataset	dataset	NOUN
ijassa-1442	288	3	.	.	PUNCT
ijassa-1442	289	1	δdp	δdp	NOUN
ijassa-1442	289	2	model	model	PROPN
ijassa-1442	289	3	privacy	privacy	NOUN
ijassa-1442	289	4	adversary	adversary	NOUN
ijassa-1442	289	5	min	min	PROPN
ijassa-1442	289	6	max	max	PROPN
ijassa-1442	289	7	mean	mean	VERB
ijassa-1442	289	8	laftr	laftr	ADV
ijassa-1442	289	9	-	-	PUNCT
ijassa-1442	289	10	dp	dp	NOUN
ijassa-1442	289	11	no	no	DET
ijassa-1442	289	12	privacy	privacy	NOUN
ijassa-1442	289	13	adversary	adversary	NOUN
ijassa-1442	289	14	=	=	SYM
ijassa-1442	289	15	classifier	classifier	NOUN
ijassa-1442	289	16	0.064	0.064	NUM
ijassa-1442	289	17	0.136	0.136	NUM
ijassa-1442	289	18	0.097	0.097	NUM
ijassa-1442	289	19	adversary	adversary	NOUN
ijassa-1442	289	20	>	>	X
ijassa-1442	289	21	classifier	classifier	NOUN
ijassa-1442	289	22	0.020	0.020	NUM
ijassa-1442	289	23	0.097	0.097	NUM
ijassa-1442	289	24	0.060	0.060	NUM
ijassa-1442	289	25	privacy	privacy	NOUN
ijassa-1442	289	26	in	in	ADP
ijassa-1442	289	27	..	..	PUNCT
ijassa-1442	289	28	adversary	adversary	NOUN
ijassa-1442	289	29	=	=	SYM
ijassa-1442	289	30	classifier	classifier	NOUN
ijassa-1442	289	31	0.000	0.000	NUM
ijassa-1442	289	32	0.163	0.163	NUM
ijassa-1442	289	33	0.059	0.059	NUM
ijassa-1442	289	34	adversary	adversary	NOUN
ijassa-1442	289	35	>	>	X
ijassa-1442	289	36	classifier	classifier	NOUN
ijassa-1442	289	37	0.001	0.001	NUM
ijassa-1442	289	38	0.140	0.140	NUM
ijassa-1442	289	39	0.057	0.057	NUM
ijassa-1442	289	40	laftr	laftr	ADJ
ijassa-1442	289	41	-	-	PUNCT
ijassa-1442	289	42	eod	eod	NOUN
ijassa-1442	289	43	no	no	DET
ijassa-1442	289	44	privacy	privacy	NOUN
ijassa-1442	289	45	adversary	adversary	NOUN
ijassa-1442	289	46	=	=	SYM
ijassa-1442	289	47	classifier	classifier	NOUN
ijassa-1442	289	48	0.017	0.017	NUM
ijassa-1442	289	49	0.133	0.133	NUM
ijassa-1442	289	50	0.080	0.080	NUM
ijassa-1442	289	51	adversary	adversary	NOUN
ijassa-1442	289	52	>	>	X
ijassa-1442	289	53	classifier	classifier	PROPN
ijassa-1442	289	54	0.046	0.046	NUM
ijassa-1442	289	55	0.143	0.143	NUM
ijassa-1442	289	56	0.081	0.081	NUM
ijassa-1442	289	57	privacy	privacy	NOUN
ijassa-1442	289	58	in	in	ADP
ijassa-1442	289	59	..	..	PUNCT
ijassa-1442	289	60	adversary	adversary	NOUN
ijassa-1442	289	61	=	=	NOUN
ijassa-1442	289	62	classifier	classifier	NOUN
ijassa-1442	289	63	0.005	0.005	NUM
ijassa-1442	289	64	0.145	0.145	NUM
ijassa-1442	289	65	0.061	0.061	NUM
ijassa-1442	289	66	adversary	adversary	NOUN
ijassa-1442	289	67	>	>	X
ijassa-1442	289	68	classifier	classifier	NOUN
ijassa-1442	289	69	0.000	0.000	NUM
ijassa-1442	289	70	0.152	0.152	NUM
ijassa-1442	289	71	0.057	0.057	NUM
ijassa-1442	289	72	unfair	unfair	ADJ
ijassa-1442	289	73	no	no	DET
ijassa-1442	289	74	privacy	privacy	NOUN
ijassa-1442	289	75	0.169	0.169	NUM
ijassa-1442	289	76	0.169	0.169	NUM
ijassa-1442	289	77	0.169	0.169	NUM
ijassa-1442	289	78	5.3	5.3	NUM
ijassa-1442	289	79	.	.	PUNCT
ijassa-1442	289	80	difference	difference	NOUN
ijassa-1442	289	81	of	of	ADP
ijassa-1442	289	82	equalized	equalize	VERB
ijassa-1442	289	83	odds	odd	NOUN
ijassa-1442	289	84	next	next	ADP
ijassa-1442	289	85	step	step	NOUN
ijassa-1442	289	86	–	–	PUNCT
ijassa-1442	289	87	results	result	NOUN
ijassa-1442	289	88	of	of	ADP
ijassa-1442	289	89	measuring	measure	VERB
ijassa-1442	289	90	second	second	ADJ
ijassa-1442	289	91	fair	fair	ADJ
ijassa-1442	289	92	metric	metric	ADJ
ijassa-1442	289	93	difference	difference	NOUN
ijassa-1442	289	94	of	of	ADP
ijassa-1442	289	95	equalized	equalize	VERB
ijassa-1442	289	96	odds	odd	NOUN
ijassa-1442	289	97	.	.	PUNCT
ijassa-1442	290	1	it	it	PRON
ijassa-1442	290	2	is	be	AUX
ijassa-1442	290	3	very	very	ADV
ijassa-1442	290	4	difficult	difficult	ADJ
ijassa-1442	290	5	to	to	PART
ijassa-1442	290	6	draw	draw	VERB
ijassa-1442	290	7	any	any	DET
ijassa-1442	290	8	conclusions	conclusion	NOUN
ijassa-1442	290	9	based	base	VERB
ijassa-1442	290	10	on	on	ADP
ijassa-1442	290	11	the	the	DET
ijassa-1442	290	12	fig	fig	NOUN
ijassa-1442	290	13	.	.	PUNCT
ijassa-1442	291	1	3	3	X
ijassa-1442	291	2	.	.	PUNCT
ijassa-1442	291	3	based	base	VERB
ijassa-1442	291	4	on	on	ADP
ijassa-1442	291	5	table	table	NOUN
ijassa-1442	291	6	5	5	NUM
ijassa-1442	291	7	,	,	PUNCT
ijassa-1442	291	8	in	in	ADP
ijassa-1442	291	9	the	the	DET
ijassa-1442	291	10	case	case	NOUN
ijassa-1442	291	11	of	of	ADP
ijassa-1442	291	12	,	,	PUNCT
ijassa-1442	291	13	the	the	DET
ijassa-1442	291	14	situation	situation	NOUN
ijassa-1442	291	15	is	be	AUX
ijassa-1442	291	16	slightly	slightly	ADV
ijassa-1442	291	17	different	different	ADJ
ijassa-1442	291	18	in	in	ADP
ijassa-1442	291	19	comparisaon	comparisaon	PROPN
ijassa-1442	291	20	with	with	ADP
ijassa-1442	291	21	.	.	PUNCT
ijassa-1442	292	1	the	the	DET
ijassa-1442	292	2	strengthening	strengthening	NOUN
ijassa-1442	292	3	of	of	ADP
ijassa-1442	292	4	the	the	DET
ijassa-1442	292	5	adversary	adversary	NOUN
ijassa-1442	292	6	continues	continue	VERB
ijassa-1442	292	7	to	to	PART
ijassa-1442	292	8	have	have	VERB
ijassa-1442	292	9	a	a	DET
ijassa-1442	292	10	positive	positive	ADJ
ijassa-1442	292	11	impact	impact	NOUN
ijassa-1442	292	12	on	on	ADP
ijassa-1442	292	13	fairness	fairness	NOUN
ijassa-1442	292	14	and	and	CCONJ
ijassa-1442	292	15	often	often	ADV
ijassa-1442	292	16	allows	allow	VERB
ijassa-1442	292	17	for	for	ADP
ijassa-1442	292	18	an	an	DET
ijassa-1442	292	19	additional	additional	ADJ
ijassa-1442	292	20	1	1	NUM
ijassa-1442	292	21	-	-	SYM
ijassa-1442	292	22	2	2	NUM
ijassa-1442	292	23	%	%	NOUN
ijassa-1442	292	24	improvement	improvement	NOUN
ijassa-1442	292	25	on	on	ADP
ijassa-1442	292	26	average	average	ADJ
ijassa-1442	292	27	.	.	PUNCT
ijassa-1442	293	1	furthermore	furthermore	ADV
ijassa-1442	293	2	,	,	PUNCT
ijassa-1442	293	3	all	all	DET
ijassa-1442	293	4	protected	protect	VERB
ijassa-1442	293	5	models	model	NOUN
ijassa-1442	293	6	can	can	AUX
ijassa-1442	293	7	achieve	achieve	VERB
ijassa-1442	293	8	better	well	ADJ
ijassa-1442	293	9	results	result	NOUN
ijassa-1442	293	10	than	than	ADP
ijassa-1442	293	11	their	their	PRON
ijassa-1442	293	12	unprotected	unprotected	ADJ
ijassa-1442	293	13	counterparts	counterpart	NOUN
ijassa-1442	293	14	.	.	PUNCT
ijassa-1442	294	1	however	however	ADV
ijassa-1442	294	2	,	,	PUNCT
ijassa-1442	294	3	in	in	ADP
ijassa-1442	294	4	the	the	DET
ijassa-1442	294	5	case	case	NOUN
ijassa-1442	294	6	of	of	ADP
ijassa-1442	294	7	,	,	PUNCT
ijassa-1442	294	8	techniques	technique	NOUN
ijassa-1442	294	9	such	such	ADJ
ijassa-1442	294	10	as	as	ADP
ijassa-1442	294	11	adversary	adversary	NOUN
ijassa-1442	294	12	strengthening	strengthening	NOUN
ijassa-1442	294	13	or	or	CCONJ
ijassa-1442	294	14	privacy	privacy	NOUN
ijassa-1442	294	15	injection	injection	NOUN
ijassa-1442	294	16	can	can	AUX
ijassa-1442	294	17	significantly	significantly	ADV
ijassa-1442	294	18	deteriorate	deteriorate	VERB
ijassa-1442	294	19	the	the	DET
ijassa-1442	294	20	outcomes	outcome	NOUN
ijassa-1442	294	21	.	.	PUNCT
ijassa-1442	295	1	for	for	ADP
ijassa-1442	295	2	instance	instance	NOUN
ijassa-1442	295	3	,	,	PUNCT
ijassa-1442	295	4	in	in	ADP
ijassa-1442	295	5	the	the	DET
ijassa-1442	295	6	laftr	laftr	ADJ
ijassa-1442	295	7	-	-	PUNCT
ijassa-1442	295	8	dp	dp	NOUN
ijassa-1442	295	9	model	model	NOUN
ijassa-1442	295	10	,	,	PUNCT
ijassa-1442	295	11	the	the	DET
ijassa-1442	295	12	addition	addition	NOUN
ijassa-1442	295	13	of	of	ADP
ijassa-1442	295	14	a	a	DET
ijassa-1442	295	15	strong	strong	ADJ
ijassa-1442	295	16	adversary	adversary	NOUN
ijassa-1442	295	17	can	can	AUX
ijassa-1442	295	18	lead	lead	VERB
ijassa-1442	295	19	to	to	ADP
ijassa-1442	295	20	results	result	NOUN
ijassa-1442	295	21	that	that	PRON
ijassa-1442	295	22	are	be	AUX
ijassa-1442	295	23	5	5	NUM
ijassa-1442	295	24	%	%	NOUN
ijassa-1442	295	25	worse	bad	ADJ
ijassa-1442	295	26	than	than	ADP
ijassa-1442	295	27	the	the	DET
ijassa-1442	295	28	unfair	unfair	ADJ
ijassa-1442	295	29	model	model	NOUN
ijassa-1442	295	30	,	,	PUNCT
ijassa-1442	295	31	and	and	CCONJ
ijassa-1442	295	32	introducing	introduce	VERB
ijassa-1442	295	33	noise	noise	NOUN
ijassa-1442	295	34	can	can	AUX
ijassa-1442	295	35	increase	increase	VERB
ijassa-1442	295	36	the	the	DET
ijassa-1442	295	37	difference	difference	NOUN
ijassa-1442	295	38	up	up	ADP
ijassa-1442	295	39	to	to	PART
ijassa-1442	295	40	22	22	NUM
ijassa-1442	295	41	%	%	NOUN
ijassa-1442	295	42	in	in	ADP
ijassa-1442	295	43	the	the	DET
ijassa-1442	295	44	worst	bad	ADJ
ijassa-1442	295	45	case	case	NOUN
ijassa-1442	295	46	.	.	PUNCT
ijassa-1442	296	1	nevertheless	nevertheless	ADV
ijassa-1442	296	2	,	,	PUNCT
ijassa-1442	296	3	the	the	DET
ijassa-1442	296	4	average	average	ADJ
ijassa-1442	296	5	values	value	NOUN
ijassa-1442	296	6	are	be	AUX
ijassa-1442	296	7	still	still	ADV
ijassa-1442	296	8	lower	low	ADJ
ijassa-1442	296	9	than	than	ADP
ijassa-1442	296	10	those	those	PRON
ijassa-1442	296	11	of	of	ADP
ijassa-1442	296	12	the	the	DET
ijassa-1442	296	13	unfair	unfair	ADJ
ijassa-1442	296	14	approach	approach	NOUN
ijassa-1442	296	15	,	,	PUNCT
ijassa-1442	296	16	but	but	CCONJ
ijassa-1442	296	17	the	the	DET
ijassa-1442	296	18	introduction	introduction	NOUN
ijassa-1442	296	19	of	of	ADP
ijassa-1442	296	20	noise	noise	NOUN
ijassa-1442	296	21	brings	bring	VERB
ijassa-1442	296	22	the	the	DET
ijassa-1442	296	23	average	average	ADJ
ijassa-1442	296	24	values	value	NOUN
ijassa-1442	296	25	closer	close	ADV
ijassa-1442	296	26	to	to	ADP
ijassa-1442	296	27	those	those	PRON
ijassa-1442	296	28	of	of	ADP
ijassa-1442	296	29	the	the	DET
ijassa-1442	296	30	unfair	unfair	ADJ
ijassa-1442	296	31	solution	solution	NOUN
ijassa-1442	296	32	,	,	PUNCT
ijassa-1442	296	33	with	with	ADP
ijassa-1442	296	34	a	a	DET
ijassa-1442	296	35	difference	difference	NOUN
ijassa-1442	296	36	of	of	ADP
ijassa-1442	296	37	1	1	NUM
ijassa-1442	296	38	-	-	SYM
ijassa-1442	296	39	2	2	NUM
ijassa-1442	296	40	%	%	NOUN
ijassa-1442	296	41	.	.	PUNCT
ijassa-1442	297	1	in	in	ADP
ijassa-1442	297	2	contrast	contrast	NOUN
ijassa-1442	297	3	,	,	PUNCT
ijassa-1442	297	4	for	for	ADP
ijassa-1442	297	5	nonprivate	nonprivate	NOUN
ijassa-1442	297	6	models	model	NOUN
ijassa-1442	297	7	,	,	PUNCT
ijassa-1442	297	8	the	the	DET
ijassa-1442	297	9	difference	difference	NOUN
ijassa-1442	297	10	ranges	range	VERB
ijassa-1442	297	11	from	from	ADP
ijassa-1442	297	12	3.6	3.6	NUM
ijassa-1442	297	13	%	%	NOUN
ijassa-1442	297	14	to	to	ADP
ijassa-1442	297	15	2.6	2.6	NUM
ijassa-1442	297	16	%	%	NOUN
ijassa-1442	297	17	.	.	PUNCT
ijassa-1442	298	1	the	the	DET
ijassa-1442	298	2	behavior	behavior	NOUN
ijassa-1442	298	3	of	of	ADP
ijassa-1442	298	4	the	the	DET
ijassa-1442	298	5	results	result	NOUN
ijassa-1442	298	6	in	in	ADP
ijassa-1442	298	7	laftr	laftr	ADJ
ijassa-1442	298	8	-	-	PUNCT
ijassa-1442	298	9	eod	eod	NOUN
ijassa-1442	298	10	models	model	NOUN
ijassa-1442	298	11	is	be	AUX
ijassa-1442	298	12	similar	similar	ADJ
ijassa-1442	298	13	to	to	ADP
ijassa-1442	298	14	laftr	laftr	NOUN
ijassa-1442	298	15	-	-	PUNCT
ijassa-1442	298	16	dp	dp	NOUN
ijassa-1442	298	17	,	,	PUNCT
ijassa-1442	298	18	but	but	CCONJ
ijassa-1442	298	19	they	they	PRON
ijassa-1442	298	20	exhibit	exhibit	VERB
ijassa-1442	298	21	less	less	ADJ
ijassa-1442	298	22	stability	stability	NOUN
ijassa-1442	298	23	.	.	PUNCT
ijassa-1442	299	1	the	the	DET
ijassa-1442	299	2	minimum	minimum	ADJ
ijassa-1442	299	3	values	value	NOUN
ijassa-1442	299	4	are	be	AUX
ijassa-1442	299	5	lower	low	ADJ
ijassa-1442	299	6	in	in	ADP
ijassa-1442	299	7	almost	almost	ADV
ijassa-1442	299	8	all	all	PRON
ijassa-1442	299	9	cases	case	NOUN
ijassa-1442	299	10	,	,	PUNCT
ijassa-1442	299	11	while	while	SCONJ
ijassa-1442	299	12	the	the	DET
ijassa-1442	299	13	maximum	maximum	ADJ
ijassa-1442	299	14	values	value	NOUN
ijassa-1442	299	15	are	be	AUX
ijassa-1442	299	16	consistently	consistently	ADV
ijassa-1442	299	17	high	high	ADJ
ijassa-1442	299	18	,	,	PUNCT
ijassa-1442	299	19	even	even	ADV
ijassa-1442	299	20	in	in	ADP
ijassa-1442	299	21	the	the	DET
ijassa-1442	299	22	case	case	NOUN
ijassa-1442	299	23	of	of	ADP
ijassa-1442	299	24	a	a	DET
ijassa-1442	299	25	weak	weak	ADJ
ijassa-1442	299	26	adversary	adversary	NOUN
ijassa-1442	299	27	without	without	ADP
ijassa-1442	299	28	protection	protection	NOUN
ijassa-1442	299	29	(	(	PUNCT
ijassa-1442	299	30	unfair	unfair	ADJ
ijassa-1442	299	31	approach	approach	NOUN
ijassa-1442	299	32	performs	perform	VERB
ijassa-1442	299	33	better	well	ADV
ijassa-1442	299	34	by	by	ADP
ijassa-1442	299	35	7	7	NUM
ijassa-1442	299	36	%	%	NOUN
ijassa-1442	299	37	)	)	PUNCT
ijassa-1442	299	38	.	.	PUNCT
ijassa-1442	300	1	in	in	ADP
ijassa-1442	300	2	other	other	ADJ
ijassa-1442	300	3	cases	case	NOUN
ijassa-1442	300	4	,	,	PUNCT
ijassa-1442	300	5	the	the	DET
ijassa-1442	300	6	difference	difference	NOUN
ijassa-1442	300	7	can	can	AUX
ijassa-1442	300	8	reach	reach	VERB
ijassa-1442	300	9	up	up	ADP
ijassa-1442	300	10	to	to	PART
ijassa-1442	300	11	19	19	NUM
ijassa-1442	300	12	%	%	NOUN
ijassa-1442	300	13	.	.	PUNCT
ijassa-1442	301	1	due	due	ADP
ijassa-1442	301	2	to	to	ADP
ijassa-1442	301	3	the	the	DET
ijassa-1442	301	4	higher	high	ADJ
ijassa-1442	301	5	instability	instability	NOUN
ijassa-1442	301	6	and	and	CCONJ
ijassa-1442	301	7	a	a	DET
ijassa-1442	301	8	larger	large	ADJ
ijassa-1442	301	9	number	number	NOUN
ijassa-1442	301	10	of	of	ADP
ijassa-1442	301	11	unfair	unfair	ADJ
ijassa-1442	301	12	results	result	NOUN
ijassa-1442	301	13	,	,	PUNCT
ijassa-1442	301	14	the	the	DET
ijassa-1442	301	15	fairness	fairness	NOUN
ijassa-1442	301	16	metric	metric	NOUN
ijassa-1442	301	17	's	's	PART
ijassa-1442	301	18	average	average	ADJ
ijassa-1442	301	19	value	value	NOUN
ijassa-1442	301	20	for	for	ADP
ijassa-1442	301	21	laftr	laftr	NOUN
ijassa-1442	301	22	-	-	PUNCT
ijassa-1442	301	23	eod	eod	NOUN
ijassa-1442	301	24	is	be	AUX
ijassa-1442	301	25	approximately	approximately	ADV
ijassa-1442	301	26	2.5	2.5	NUM
ijassa-1442	301	27	%	%	NOUN
ijassa-1442	301	28	worse	bad	ADJ
ijassa-1442	301	29	than	than	ADP
ijassa-1442	301	30	that	that	PRON
ijassa-1442	301	31	of	of	ADP
ijassa-1442	301	32	laftr	laftr	NOUN
ijassa-1442	301	33	-	-	PUNCT
ijassa-1442	301	34	dp	dp	NOUN
ijassa-1442	301	35	.	.	NOUN
ijassa-1442	301	36	52	52	NUM
ijassa-1442	301	37	a.	a.	NOUN
ijassa-1442	301	38	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	301	39	,	,	PUNCT
ijassa-1442	301	40	r.	r.	PROPN
ijassa-1442	301	41	sabitov	sabitov	PROPN
ijassa-1442	301	42	,	,	PUNCT
ijassa-1442	301	43	g.	g.	PROPN
ijassa-1442	301	44	smirnova	smirnova	PROPN
ijassa-1442	301	45	,	,	PUNCT
ijassa-1442	301	46	sh	sh	PROPN
ijassa-1442	301	47	.	.	PUNCT
ijassa-1442	301	48	sabitov	sabitov	PROPN
ijassa-1442	301	49	copyright	copyright	NOUN
ijassa-1442	302	1	©	©	PROPN
ijassa-1442	302	2	2023	2023	NUM
ijassa-1442	302	3	assa	assa	PROPN
ijassa-1442	302	4	adv	adv	PROPN
ijassa-1442	302	5	.	.	PUNCT
ijassa-1442	303	1	in	in	ADP
ijassa-1442	303	2	systems	system	NOUN
ijassa-1442	303	3	science	science	NOUN
ijassa-1442	303	4	and	and	CCONJ
ijassa-1442	303	5	appl	appl	NOUN
ijassa-1442	303	6	.	.	PUNCT
ijassa-1442	304	1	(	(	PUNCT
ijassa-1442	304	2	2023	2023	NUM
ijassa-1442	304	3	)	)	PUNCT
ijassa-1442	304	4	fig	fig	NOUN
ijassa-1442	304	5	.	.	PUNCT
ijassa-1442	305	1	3	3	X
ijassa-1442	305	2	.	.	X
ijassa-1442	305	3	dependence	dependence	NOUN
ijassa-1442	305	4	of	of	ADP
ijassa-1442	305	5	on	on	ADP
ijassa-1442	305	6	for	for	ADP
ijassa-1442	305	7	adult	adult	NOUN
ijassa-1442	305	8	dataset	dataset	NOUN
ijassa-1442	305	9	table	table	NOUN
ijassa-1442	305	10	5	5	NUM
ijassa-1442	305	11	comparison	comparison	NOUN
ijassa-1442	305	12	.	.	PUNCT
ijassa-1442	306	1	adult	adult	NOUN
ijassa-1442	306	2	dataset	dataset	NOUN
ijassa-1442	306	3	.	.	PUNCT
ijassa-1442	307	1	δeod	δeod	NOUN
ijassa-1442	307	2	model	model	PROPN
ijassa-1442	307	3	privacy	privacy	NOUN
ijassa-1442	307	4	adversary	adversary	NOUN
ijassa-1442	307	5	min	min	PROPN
ijassa-1442	307	6	max	max	PROPN
ijassa-1442	307	7	mean	mean	VERB
ijassa-1442	307	8	laftr	laftr	ADV
ijassa-1442	307	9	-	-	PUNCT
ijassa-1442	307	10	dp	dp	NOUN
ijassa-1442	307	11	no	no	DET
ijassa-1442	307	12	privacy	privacy	NOUN
ijassa-1442	307	13	adversary	adversary	NOUN
ijassa-1442	307	14	=	=	SYM
ijassa-1442	307	15	classifier	classifier	NOUN
ijassa-1442	307	16	0.055	0.055	NUM
ijassa-1442	307	17	0.107	0.107	NUM
ijassa-1442	307	18	0.084	0.084	NUM
ijassa-1442	307	19	adversary	adversary	NOUN
ijassa-1442	307	20	>	>	X
ijassa-1442	307	21	classifier	classifier	NOUN
ijassa-1442	307	22	0.015	0.015	NUM
ijassa-1442	307	23	0.165	0.165	NUM
ijassa-1442	307	24	0.076	0.076	NUM
ijassa-1442	307	25	privacy	privacy	NOUN
ijassa-1442	307	26	in	in	ADP
ijassa-1442	307	27	..	..	PUNCT
ijassa-1442	307	28	adversary	adversary	NOUN
ijassa-1442	307	29	=	=	SYM
ijassa-1442	307	30	classifier	classifier	NOUN
ijassa-1442	307	31	0.008	0.008	NUM
ijassa-1442	307	32	0.335	0.335	NUM
ijassa-1442	307	33	0.103	0.103	NUM
ijassa-1442	307	34	adversary	adversary	NOUN
ijassa-1442	307	35	>	>	X
ijassa-1442	307	36	classifier	classifier	NOUN
ijassa-1442	307	37	0.010	0.010	NUM
ijassa-1442	307	38	0.317	0.317	NUM
ijassa-1442	307	39	0.092	0.092	NUM
ijassa-1442	307	40	laftr	laftr	ADJ
ijassa-1442	307	41	-	-	PUNCT
ijassa-1442	307	42	eod	eod	NOUN
ijassa-1442	307	43	no	no	DET
ijassa-1442	307	44	privacy	privacy	NOUN
ijassa-1442	307	45	adversary	adversary	NOUN
ijassa-1442	307	46	=	=	SYM
ijassa-1442	307	47	classifier	classifier	NOUN
ijassa-1442	307	48	0.027	0.027	NUM
ijassa-1442	307	49	0.183	0.183	NUM
ijassa-1442	307	50	0.114	0.114	NUM
ijassa-1442	307	51	adversary	adversary	NOUN
ijassa-1442	307	52	>	>	X
ijassa-1442	307	53	classifier	classifier	NOUN
ijassa-1442	307	54	0.042	0.042	NUM
ijassa-1442	307	55	0.205	0.205	NUM
ijassa-1442	307	56	0.107	0.107	NUM
ijassa-1442	307	57	privacy	privacy	NOUN
ijassa-1442	307	58	in	in	ADP
ijassa-1442	307	59	..	..	PUNCT
ijassa-1442	307	60	adversary	adversary	NOUN
ijassa-1442	307	61	=	=	SYM
ijassa-1442	307	62	classifier	classifier	NOUN
ijassa-1442	307	63	0.006	0.006	NUM
ijassa-1442	307	64	0.309	0.309	NUM
ijassa-1442	307	65	0.113	0.113	NUM
ijassa-1442	307	66	adversary	adversary	NOUN
ijassa-1442	307	67	>	>	X
ijassa-1442	307	68	classifier	classifier	NOUN
ijassa-1442	307	69	0.007	0.007	NUM
ijassa-1442	307	70	0.276	0.276	NUM
ijassa-1442	307	71	0.090	0.090	NUM
ijassa-1442	307	72	unfair	unfair	ADJ
ijassa-1442	307	73	no	no	DET
ijassa-1442	307	74	privacy	privacy	NOUN
ijassa-1442	307	75	0.117	0.117	NUM
ijassa-1442	307	76	0.117	0.117	NUM
ijassa-1442	307	77	0.117	0.117	NUM
ijassa-1442	307	78	5.4	5.4	NUM
ijassa-1442	307	79	.	.	PUNCT
ijassa-1442	308	1	accuracy	accuracy	NOUN
ijassa-1442	308	2	to	to	PART
ijassa-1442	308	3	fully	fully	ADV
ijassa-1442	308	4	understand	understand	VERB
ijassa-1442	308	5	the	the	DET
ijassa-1442	308	6	behavior	behavior	NOUN
ijassa-1442	308	7	of	of	ADP
ijassa-1442	308	8	the	the	DET
ijassa-1442	308	9	model	model	NOUN
ijassa-1442	308	10	,	,	PUNCT
ijassa-1442	308	11	it	it	PRON
ijassa-1442	308	12	is	be	AUX
ijassa-1442	308	13	necessary	necessary	ADJ
ijassa-1442	308	14	to	to	PART
ijassa-1442	308	15	investigate	investigate	VERB
ijassa-1442	308	16	patterns	pattern	NOUN
ijassa-1442	308	17	of	of	ADP
ijassa-1442	308	18	accuracy	accuracy	NOUN
ijassa-1442	308	19	.	.	PUNCT
ijassa-1442	309	1	balancing	balance	VERB
ijassa-1442	309	2	accuracy	accuracy	NOUN
ijassa-1442	309	3	,	,	PUNCT
ijassa-1442	309	4	fairness	fairness	NOUN
ijassa-1442	309	5	and	and	CCONJ
ijassa-1442	309	6	privacy	privacy	NOUN
ijassa-1442	309	7	in	in	ADP
ijassa-1442	309	8	machine	machine	NOUN
ijassa-1442	309	9	learning	learning	NOUN
ijassa-1442	309	10	…	…	PUNCT
ijassa-1442	309	11	53	53	NUM
ijassa-1442	309	12	copyright	copyright	NOUN
ijassa-1442	309	13	©	©	PROPN
ijassa-1442	309	14	2023	2023	NUM
ijassa-1442	309	15	assa	assa	NOUN
ijassa-1442	309	16	.	.	PUNCT
ijassa-1442	310	1	adv	adv	PROPN
ijassa-1442	310	2	.	.	PUNCT
ijassa-1442	311	1	in	in	ADP
ijassa-1442	311	2	systems	system	NOUN
ijassa-1442	311	3	science	science	NOUN
ijassa-1442	311	4	and	and	CCONJ
ijassa-1442	311	5	appl	appl	NOUN
ijassa-1442	311	6	.	.	PUNCT
ijassa-1442	312	1	(	(	PUNCT
ijassa-1442	312	2	2023	2023	NUM
ijassa-1442	312	3	)	)	PUNCT
ijassa-1442	312	4	as	as	ADP
ijassa-1442	312	5	in	in	ADP
ijassa-1442	312	6	demographical	demographical	ADJ
ijassa-1442	312	7	parity	parity	NOUN
ijassa-1442	312	8	metric	metric	ADJ
ijassa-1442	312	9	fig	fig	NOUN
ijassa-1442	312	10	.	.	PUNCT
ijassa-1442	313	1	4	4	NUM
ijassa-1442	313	2	demonstrates	demonstrate	VERB
ijassa-1442	313	3	that	that	SCONJ
ijassa-1442	313	4	the	the	DET
ijassa-1442	313	5	"	"	PUNCT
ijassa-1442	313	6	unfair	unfair	ADJ
ijassa-1442	313	7	"	"	PUNCT
ijassa-1442	313	8	model	model	NOUN
ijassa-1442	313	9	,	,	PUNCT
ijassa-1442	313	10	which	which	PRON
ijassa-1442	313	11	has	have	VERB
ijassa-1442	313	12	no	no	DET
ijassa-1442	313	13	privacy	privacy	NOUN
ijassa-1442	313	14	protection	protection	NOUN
ijassa-1442	313	15	and	and	CCONJ
ijassa-1442	313	16	an	an	DET
ijassa-1442	313	17	unfair	unfair	ADJ
ijassa-1442	313	18	adversary	adversary	NOUN
ijassa-1442	313	19	much	much	ADV
ijassa-1442	313	20	better	well	ADV
ijassa-1442	313	21	predict	predict	VERB
ijassa-1442	313	22	labels	label	NOUN
ijassa-1442	313	23	and	and	CCONJ
ijassa-1442	313	24	consistently	consistently	ADV
ijassa-1442	313	25	outperformed	outperform	VERB
ijassa-1442	313	26	by	by	ADP
ijassa-1442	313	27	all	all	DET
ijassa-1442	313	28	other	other	ADJ
ijassa-1442	313	29	models	model	NOUN
ijassa-1442	313	30	in	in	ADP
ijassa-1442	313	31	terms	term	NOUN
ijassa-1442	313	32	of	of	ADP
ijassa-1442	313	33	accuracy	accuracy	NOUN
ijassa-1442	313	34	.	.	PUNCT
ijassa-1442	314	1	fig	fig	NOUN
ijassa-1442	314	2	.	.	PUNCT
ijassa-1442	315	1	4	4	X
ijassa-1442	315	2	.	.	X
ijassa-1442	315	3	dependence	dependence	NOUN
ijassa-1442	315	4	of	of	ADP
ijassa-1442	315	5	accuracy	accuracy	NOUN
ijassa-1442	315	6	on	on	ADP
ijassa-1442	315	7	for	for	ADP
ijassa-1442	315	8	adult	adult	NOUN
ijassa-1442	315	9	dataset	dataset	NOUN
ijassa-1442	315	10	as	as	SCONJ
ijassa-1442	315	11	shown	show	VERB
ijassa-1442	315	12	in	in	ADP
ijassa-1442	315	13	table	table	NOUN
ijassa-1442	315	14	6	6	NUM
ijassa-1442	315	15	,	,	PUNCT
ijassa-1442	315	16	the	the	DET
ijassa-1442	315	17	average	average	ADJ
ijassa-1442	315	18	accuracy	accuracy	NOUN
ijassa-1442	315	19	values	value	NOUN
ijassa-1442	315	20	are	be	AUX
ijassa-1442	315	21	independent	independent	ADJ
ijassa-1442	315	22	of	of	ADP
ijassa-1442	315	23	the	the	DET
ijassa-1442	315	24	adversary	adversary	NOUN
ijassa-1442	315	25	's	's	PART
ijassa-1442	315	26	strength	strength	NOUN
ijassa-1442	315	27	and	and	CCONJ
ijassa-1442	315	28	the	the	DET
ijassa-1442	315	29	model	model	NOUN
ijassa-1442	315	30	type	type	NOUN
ijassa-1442	315	31	.	.	PUNCT
ijassa-1442	316	1	the	the	DET
ijassa-1442	316	2	only	only	ADJ
ijassa-1442	316	3	factor	factor	NOUN
ijassa-1442	316	4	that	that	PRON
ijassa-1442	316	5	leads	lead	VERB
ijassa-1442	316	6	to	to	ADP
ijassa-1442	316	7	a	a	DET
ijassa-1442	316	8	decrease	decrease	NOUN
ijassa-1442	316	9	in	in	ADP
ijassa-1442	316	10	accuracy	accuracy	NOUN
ijassa-1442	316	11	of	of	ADP
ijassa-1442	316	12	around	around	ADV
ijassa-1442	316	13	23	23	NUM
ijassa-1442	316	14	%	%	NOUN
ijassa-1442	316	15	is	be	AUX
ijassa-1442	316	16	the	the	DET
ijassa-1442	316	17	introduction	introduction	NOUN
ijassa-1442	316	18	of	of	ADP
ijassa-1442	316	19	privacy	privacy	NOUN
ijassa-1442	316	20	.	.	PUNCT
ijassa-1442	317	1	the	the	DET
ijassa-1442	317	2	difference	difference	NOUN
ijassa-1442	317	3	between	between	ADP
ijassa-1442	317	4	the	the	DET
ijassa-1442	317	5	minimum	minimum	ADJ
ijassa-1442	317	6	and	and	CCONJ
ijassa-1442	317	7	maximum	maximum	ADJ
ijassa-1442	317	8	accuracy	accuracy	NOUN
ijassa-1442	317	9	values	value	NOUN
ijassa-1442	317	10	varies	vary	VERB
ijassa-1442	317	11	between	between	ADP
ijassa-1442	317	12	4	4	NUM
ijassa-1442	317	13	%	%	NOUN
ijassa-1442	317	14	and	and	CCONJ
ijassa-1442	317	15	7	7	NUM
ijassa-1442	317	16	%	%	NOUN
ijassa-1442	317	17	,	,	PUNCT
ijassa-1442	317	18	and	and	CCONJ
ijassa-1442	317	19	these	these	DET
ijassa-1442	317	20	values	value	NOUN
ijassa-1442	317	21	do	do	AUX
ijassa-1442	317	22	not	not	PART
ijassa-1442	317	23	exhibit	exhibit	VERB
ijassa-1442	317	24	any	any	DET
ijassa-1442	317	25	clear	clear	ADJ
ijassa-1442	317	26	correlation	correlation	NOUN
ijassa-1442	317	27	.	.	PUNCT
ijassa-1442	318	1	in	in	ADP
ijassa-1442	318	2	general	general	ADJ
ijassa-1442	318	3	,	,	PUNCT
ijassa-1442	318	4	non	non	ADJ
ijassa-1442	318	5	-	-	ADJ
ijassa-1442	318	6	private	private	ADJ
ijassa-1442	318	7	models	model	NOUN
ijassa-1442	318	8	demonstrate	demonstrate	VERB
ijassa-1442	318	9	a	a	DET
ijassa-1442	318	10	5	5	NUM
ijassa-1442	318	11	%	%	NOUN
ijassa-1442	318	12	deviation	deviation	NOUN
ijassa-1442	318	13	from	from	ADP
ijassa-1442	318	14	the	the	DET
ijassa-1442	318	15	unfair	unfair	ADJ
ijassa-1442	318	16	solution	solution	NOUN
ijassa-1442	318	17	,	,	PUNCT
ijassa-1442	318	18	likely	likely	ADJ
ijassa-1442	318	19	due	due	ADP
ijassa-1442	318	20	to	to	ADP
ijassa-1442	318	21	the	the	DET
ijassa-1442	318	22	reduced	reduced	ADJ
ijassa-1442	318	23	dimensionality	dimensionality	NOUN
ijassa-1442	318	24	of	of	ADP
ijassa-1442	318	25	the	the	DET
ijassa-1442	318	26	latent	latent	NOUN
ijassa-1442	318	27	z	z	NOUN
ijassa-1442	318	28	-	-	PUNCT
ijassa-1442	318	29	space	space	NOUN
ijassa-1442	318	30	and	and	CCONJ
ijassa-1442	318	31	the	the	DET
ijassa-1442	318	32	potential	potential	ADJ
ijassa-1442	318	33	loss	loss	NOUN
ijassa-1442	318	34	of	of	ADP
ijassa-1442	318	35	information	information	NOUN
ijassa-1442	318	36	during	during	ADP
ijassa-1442	318	37	data	data	NOUN
ijassa-1442	318	38	encoding	encoding	NOUN
ijassa-1442	318	39	.	.	PUNCT
ijassa-1442	319	1	protected	protect	VERB
ijassa-1442	319	2	models	model	NOUN
ijassa-1442	319	3	show	show	VERB
ijassa-1442	319	4	an	an	DET
ijassa-1442	319	5	8	8	NUM
ijassa-1442	319	6	%	%	NOUN
ijassa-1442	319	7	deviation	deviation	NOUN
ijassa-1442	319	8	,	,	PUNCT
ijassa-1442	319	9	which	which	PRON
ijassa-1442	319	10	can	can	AUX
ijassa-1442	319	11	be	be	AUX
ijassa-1442	319	12	attributed	attribute	VERB
ijassa-1442	319	13	to	to	ADP
ijassa-1442	319	14	the	the	DET
ijassa-1442	319	15	addition	addition	NOUN
ijassa-1442	319	16	of	of	ADP
ijassa-1442	319	17	noise	noise	NOUN
ijassa-1442	319	18	in	in	ADP
ijassa-1442	319	19	the	the	DET
ijassa-1442	319	20	training	training	NOUN
ijassa-1442	319	21	process	process	NOUN
ijassa-1442	319	22	,	,	PUNCT
ijassa-1442	319	23	affecting	affect	VERB
ijassa-1442	319	24	the	the	DET
ijassa-1442	319	25	latent	latent	NOUN
ijassa-1442	319	26	z	z	PROPN
ijassa-1442	319	27	-	-	PUNCT
ijassa-1442	319	28	vector	vector	NOUN
ijassa-1442	319	29	.	.	PUNCT
ijassa-1442	319	30	to	to	PART
ijassa-1442	319	31	assess	assess	VERB
ijassa-1442	319	32	the	the	DET
ijassa-1442	319	33	trade	trade	NOUN
ijassa-1442	319	34	-	-	PUNCT
ijassa-1442	319	35	off	off	NOUN
ijassa-1442	319	36	between	between	ADP
ijassa-1442	319	37	accuracy	accuracy	NOUN
ijassa-1442	319	38	and	and	CCONJ
ijassa-1442	319	39	fairness	fairness	NOUN
ijassa-1442	319	40	and	and	CCONJ
ijassa-1442	319	41	understand	understand	VERB
ijassa-1442	319	42	the	the	DET
ijassa-1442	319	43	benefits	benefit	NOUN
ijassa-1442	319	44	of	of	ADP
ijassa-1442	319	45	prioritizing	prioritize	VERB
ijassa-1442	319	46	fairness	fairness	NOUN
ijassa-1442	319	47	over	over	ADP
ijassa-1442	319	48	accuracy	accuracy	NOUN
ijassa-1442	319	49	,	,	PUNCT
ijassa-1442	319	50	it	it	PRON
ijassa-1442	319	51	is	be	AUX
ijassa-1442	319	52	crucial	crucial	ADJ
ijassa-1442	319	53	to	to	PART
ijassa-1442	319	54	examine	examine	VERB
ijassa-1442	319	55	the	the	DET
ijassa-1442	319	56	compromise	compromise	NOUN
ijassa-1442	319	57	between	between	ADP
ijassa-1442	319	58	these	these	DET
ijassa-1442	319	59	two	two	NUM
ijassa-1442	319	60	metrics	metric	NOUN
ijassa-1442	319	61	.	.	PUNCT
ijassa-1442	320	1	by	by	ADP
ijassa-1442	320	2	analyzing	analyze	VERB
ijassa-1442	320	3	the	the	DET
ijassa-1442	320	4	relationship	relationship	NOUN
ijassa-1442	320	5	between	between	ADP
ijassa-1442	320	6	accuracy	accuracy	NOUN
ijassa-1442	320	7	and	and	CCONJ
ijassa-1442	320	8	fairness	fairness	NOUN
ijassa-1442	320	9	measures	measure	NOUN
ijassa-1442	320	10	,	,	PUNCT
ijassa-1442	320	11	we	we	PRON
ijassa-1442	320	12	can	can	AUX
ijassa-1442	320	13	determine	determine	VERB
ijassa-1442	320	14	the	the	DET
ijassa-1442	320	15	extent	extent	NOUN
ijassa-1442	320	16	to	to	PART
ijassa-1442	320	17	which	which	PRON
ijassa-1442	320	18	sacrificing	sacrifice	VERB
ijassa-1442	320	19	accuracy	accuracy	NOUN
ijassa-1442	320	20	has	have	AUX
ijassa-1442	320	21	resulted	result	VERB
ijassa-1442	320	22	in	in	ADP
ijassa-1442	320	23	improved	improved	ADJ
ijassa-1442	320	24	fairness	fairness	NOUN
ijassa-1442	320	25	54	54	NUM
ijassa-1442	320	26	a.	a.	NOUN
ijassa-1442	320	27	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	320	28	,	,	PUNCT
ijassa-1442	320	29	r.	r.	PROPN
ijassa-1442	320	30	sabitov	sabitov	PROPN
ijassa-1442	320	31	,	,	PUNCT
ijassa-1442	320	32	g.	g.	PROPN
ijassa-1442	320	33	smirnova	smirnova	PROPN
ijassa-1442	320	34	,	,	PUNCT
ijassa-1442	320	35	sh	sh	PROPN
ijassa-1442	320	36	.	.	PUNCT
ijassa-1442	320	37	sabitov	sabitov	PROPN
ijassa-1442	320	38	copyright	copyright	NOUN
ijassa-1442	320	39	©	©	PROPN
ijassa-1442	320	40	2023	2023	NUM
ijassa-1442	320	41	assa	assa	PROPN
ijassa-1442	320	42	adv	adv	PROPN
ijassa-1442	320	43	.	.	PUNCT
ijassa-1442	321	1	in	in	ADP
ijassa-1442	321	2	systems	system	NOUN
ijassa-1442	321	3	science	science	NOUN
ijassa-1442	321	4	and	and	CCONJ
ijassa-1442	321	5	appl	appl	NOUN
ijassa-1442	321	6	.	.	PUNCT
ijassa-1442	322	1	(	(	PUNCT
ijassa-1442	322	2	2023	2023	NUM
ijassa-1442	322	3	)	)	PUNCT
ijassa-1442	322	4	outcomes	outcome	NOUN
ijassa-1442	322	5	.	.	PUNCT
ijassa-1442	323	1	this	this	DET
ijassa-1442	323	2	analysis	analysis	NOUN
ijassa-1442	323	3	allows	allow	VERB
ijassa-1442	323	4	us	we	PRON
ijassa-1442	323	5	to	to	PART
ijassa-1442	323	6	evaluate	evaluate	VERB
ijassa-1442	323	7	the	the	DET
ijassa-1442	323	8	value	value	NOUN
ijassa-1442	323	9	of	of	ADP
ijassa-1442	323	10	prioritizing	prioritize	VERB
ijassa-1442	323	11	fairness	fairness	NOUN
ijassa-1442	323	12	and	and	CCONJ
ijassa-1442	323	13	make	make	VERB
ijassa-1442	323	14	informed	informed	ADJ
ijassa-1442	323	15	decisions	decision	NOUN
ijassa-1442	323	16	regarding	regard	VERB
ijassa-1442	323	17	the	the	DET
ijassa-1442	323	18	trade	trade	NOUN
ijassa-1442	323	19	-	-	PUNCT
ijassa-1442	323	20	off	off	NOUN
ijassa-1442	323	21	between	between	ADP
ijassa-1442	323	22	these	these	DET
ijassa-1442	323	23	two	two	NUM
ijassa-1442	323	24	important	important	ADJ
ijassa-1442	323	25	considerations	consideration	NOUN
ijassa-1442	323	26	.	.	PUNCT
ijassa-1442	324	1	table	table	NOUN
ijassa-1442	324	2	6	6	NUM
ijassa-1442	324	3	general	general	ADJ
ijassa-1442	324	4	accuracy	accuracy	NOUN
ijassa-1442	324	5	comparison	comparison	NOUN
ijassa-1442	324	6	.	.	PUNCT
ijassa-1442	325	1	adult	adult	NOUN
ijassa-1442	325	2	dataset	dataset	NOUN
ijassa-1442	325	3	.	.	PUNCT
ijassa-1442	326	1	accuracy	accuracy	NOUN
ijassa-1442	326	2	model	model	PROPN
ijassa-1442	326	3	privacy	privacy	NOUN
ijassa-1442	326	4	adversary	adversary	NOUN
ijassa-1442	326	5	min	min	PROPN
ijassa-1442	326	6	max	max	PROPN
ijassa-1442	326	7	mean	mean	VERB
ijassa-1442	326	8	laftr	laftr	ADV
ijassa-1442	326	9	-	-	PUNCT
ijassa-1442	326	10	dp	dp	NOUN
ijassa-1442	326	11	no	no	DET
ijassa-1442	326	12	privacy	privacy	NOUN
ijassa-1442	326	13	adversary	adversary	NOUN
ijassa-1442	326	14	=	=	SYM
ijassa-1442	326	15	classifier	classifier	NOUN
ijassa-1442	326	16	0.785	0.785	NUM
ijassa-1442	326	17	0.829	0.829	NUM
ijassa-1442	326	18	0.810	0.810	NUM
ijassa-1442	326	19	adversary	adversary	NOUN
ijassa-1442	326	20	>	>	X
ijassa-1442	326	21	classifier	classifier	NOUN
ijassa-1442	326	22	0.767	0.767	NUM
ijassa-1442	326	23	0.810	0.810	NUM
ijassa-1442	326	24	0.792	0.792	NUM
ijassa-1442	326	25	privacy	privacy	NOUN
ijassa-1442	326	26	in	in	ADP
ijassa-1442	326	27	..	..	PUNCT
ijassa-1442	326	28	adversary	adversary	NOUN
ijassa-1442	326	29	=	=	NOUN
ijassa-1442	326	30	classifier	classifier	NOUN
ijassa-1442	326	31	0.749	0.749	NUM
ijassa-1442	326	32	0.803	0.803	NUM
ijassa-1442	326	33	0.777	0.777	NUM
ijassa-1442	326	34	adversary	adversary	NOUN
ijassa-1442	326	35	>	>	X
ijassa-1442	326	36	classifier	classifier	NOUN
ijassa-1442	326	37	0.749	0.749	NUM
ijassa-1442	326	38	0.805	0.805	NUM
ijassa-1442	326	39	0.777	0.777	NUM
ijassa-1442	326	40	laftr	laftr	ADJ
ijassa-1442	326	41	-	-	PUNCT
ijassa-1442	326	42	eod	eod	NOUN
ijassa-1442	326	43	no	no	DET
ijassa-1442	326	44	privacy	privacy	NOUN
ijassa-1442	326	45	adversary	adversary	NOUN
ijassa-1442	326	46	=	=	SYM
ijassa-1442	326	47	classifier	classifier	NOUN
ijassa-1442	326	48	0.758	0.758	NUM
ijassa-1442	326	49	0.830	0.830	NUM
ijassa-1442	326	50	0.803	0.803	NUM
ijassa-1442	326	51	adversary	adversary	NOUN
ijassa-1442	326	52	>	>	X
ijassa-1442	326	53	classifier	classifier	NOUN
ijassa-1442	326	54	0.784	0.784	NUM
ijassa-1442	326	55	0.823	0.823	NUM
ijassa-1442	326	56	0.804	0.804	NUM
ijassa-1442	326	57	privacy	privacy	NOUN
ijassa-1442	326	58	in	in	ADP
ijassa-1442	326	59	..	..	PUNCT
ijassa-1442	326	60	adversary	adversary	NOUN
ijassa-1442	326	61	=	=	SYM
ijassa-1442	326	62	classifier	classifier	NOUN
ijassa-1442	326	63	0.756	0.756	NUM
ijassa-1442	326	64	0.808	0.808	NUM
ijassa-1442	326	65	0.779	0.779	NUM
ijassa-1442	326	66	adversary	adversary	NOUN
ijassa-1442	326	67	>	>	X
ijassa-1442	326	68	classifier	classifier	NOUN
ijassa-1442	326	69	0.754	0.754	NUM
ijassa-1442	326	70	0.822	0.822	NUM
ijassa-1442	326	71	0.778	0.778	NUM
ijassa-1442	326	72	unfair	unfair	ADJ
ijassa-1442	326	73	no	no	DET
ijassa-1442	326	74	privacy	privacy	NOUN
ijassa-1442	326	75	0.853	0.853	NUM
ijassa-1442	326	76	0.853	0.853	NUM
ijassa-1442	326	77	0.853	0.853	NUM
ijassa-1442	326	78	5.5	5.5	NUM
ijassa-1442	326	79	.	.	PUNCT
ijassa-1442	326	80	accuracy	accuracy	NOUN
ijassa-1442	326	81	/	/	SYM
ijassa-1442	326	82	fairness	fairness	NOUN
ijassa-1442	326	83	trade	trade	NOUN
ijassa-1442	326	84	-	-	PUNCT
ijassa-1442	326	85	off	off	NOUN
ijassa-1442	326	86	we	we	PRON
ijassa-1442	326	87	compared	compare	VERB
ijassa-1442	326	88	fairness	fairness	NOUN
ijassa-1442	326	89	and	and	CCONJ
ijassa-1442	326	90	accuracy	accuracy	NOUN
ijassa-1442	326	91	of	of	ADP
ijassa-1442	326	92	different	different	ADJ
ijassa-1442	326	93	approaches	approach	NOUN
ijassa-1442	326	94	and	and	CCONJ
ijassa-1442	326	95	explored	explore	VERB
ijassa-1442	326	96	that	that	SCONJ
ijassa-1442	326	97	the	the	DET
ijassa-1442	326	98	bigger	big	ADJ
ijassa-1442	326	99	fairness	fairness	NOUN
ijassa-1442	326	100	the	the	DET
ijassa-1442	326	101	lower	low	ADJ
ijassa-1442	326	102	accuracy	accuracy	NOUN
ijassa-1442	326	103	and	and	CCONJ
ijassa-1442	326	104	vice	vice	NOUN
ijassa-1442	326	105	versa	versa	ADV
ijassa-1442	326	106	.	.	PUNCT
ijassa-1442	327	1	to	to	PART
ijassa-1442	327	2	understand	understand	VERB
ijassa-1442	327	3	advantages	advantage	NOUN
ijassa-1442	327	4	of	of	ADP
ijassa-1442	327	5	provided	provide	VERB
ijassa-1442	327	6	models	model	NOUN
ijassa-1442	327	7	we	we	PRON
ijassa-1442	327	8	need	need	VERB
ijassa-1442	327	9	to	to	PART
ijassa-1442	327	10	compare	compare	VERB
ijassa-1442	327	11	accuracy	accuracy	NOUN
ijassa-1442	327	12	-	-	PUNCT
ijassa-1442	327	13	fairness	fairness	NOUN
ijassa-1442	327	14	trade	trade	NOUN
ijassa-1442	327	15	-	-	PUNCT
ijassa-1442	327	16	off	off	NOUN
ijassa-1442	327	17	using	use	VERB
ijassa-1442	327	18	custom	custom	NOUN
ijassa-1442	327	19	metric	metric	ADJ
ijassa-1442	327	20	which	which	PRON
ijassa-1442	327	21	was	be	AUX
ijassa-1442	327	22	provided	provide	VERB
ijassa-1442	327	23	in	in	ADP
ijassa-1442	327	24	section	section	NOUN
ijassa-1442	327	25	4.4	4.4	NUM
ijassa-1442	327	26	.	.	PUNCT
ijassa-1442	328	1	the	the	DET
ijassa-1442	328	2	information	information	NOUN
ijassa-1442	328	3	presented	present	VERB
ijassa-1442	328	4	in	in	ADP
ijassa-1442	328	5	fig	fig	NOUN
ijassa-1442	328	6	.	.	PUNCT
ijassa-1442	329	1	5	5	NUM
ijassa-1442	329	2	shows	show	VERB
ijassa-1442	329	3	that	that	SCONJ
ijassa-1442	329	4	“	"	PUNCT
ijassa-1442	329	5	no	no	DET
ijassa-1442	329	6	privacy	privacy	NOUN
ijassa-1442	329	7	”	"	PUNCT
ijassa-1442	329	8	approaches	approach	VERB
ijassa-1442	329	9	slightly	slightly	ADV
ijassa-1442	329	10	better	well	ADJ
ijassa-1442	329	11	than	than	ADP
ijassa-1442	329	12	“	"	PUNCT
ijassa-1442	329	13	unfair	unfair	ADJ
ijassa-1442	329	14	”	"	PUNCT
ijassa-1442	329	15	and	and	CCONJ
ijassa-1442	329	16	protected	protect	VERB
ijassa-1442	329	17	approaches	approach	NOUN
ijassa-1442	329	18	.	.	PUNCT
ijassa-1442	330	1	but	but	CCONJ
ijassa-1442	330	2	for	for	ADP
ijassa-1442	330	3	a	a	DET
ijassa-1442	330	4	complete	complete	ADJ
ijassa-1442	330	5	picture	picture	NOUN
ijassa-1442	330	6	of	of	ADP
ijassa-1442	330	7	understanding	understand	VERB
ijassa-1442	330	8	the	the	DET
ijassa-1442	330	9	compromise	compromise	NOUN
ijassa-1442	330	10	,	,	PUNCT
ijassa-1442	330	11	it	it	PRON
ijassa-1442	330	12	is	be	AUX
ijassa-1442	330	13	also	also	ADV
ijassa-1442	330	14	necessary	necessary	ADJ
ijassa-1442	330	15	to	to	PART
ijassa-1442	330	16	compare	compare	VERB
ijassa-1442	330	17	the	the	DET
ijassa-1442	330	18	accuracy	accuracy	NOUN
ijassa-1442	330	19	-	-	PUNCT
ijassa-1442	330	20	difference	difference	NOUN
ijassa-1442	330	21	of	of	ADP
ijassa-1442	330	22	equalized	equalize	VERB
ijassa-1442	330	23	odds	odd	NOUN
ijassa-1442	330	24	trade	trade	NOUN
ijassa-1442	330	25	-	-	PUNCT
ijassa-1442	330	26	off	off	NOUN
ijassa-1442	330	27	.	.	PUNCT
ijassa-1442	331	1	it	it	PRON
ijassa-1442	331	2	is	be	AUX
ijassa-1442	331	3	evident	evident	ADJ
ijassa-1442	331	4	from	from	ADP
ijassa-1442	331	5	fig	fig	NOUN
ijassa-1442	331	6	.	.	PUNCT
ijassa-1442	332	1	6	6	NUM
ijassa-1442	332	2	that	that	SCONJ
ijassa-1442	332	3	“	"	PUNCT
ijassa-1442	332	4	unfair	unfair	ADJ
ijassa-1442	332	5	”	"	PUNCT
ijassa-1442	332	6	approach	approach	NOUN
ijassa-1442	332	7	has	have	VERB
ijassa-1442	332	8	better	well	ADJ
ijassa-1442	332	9	trade	trade	NOUN
ijassa-1442	332	10	-	-	PUNCT
ijassa-1442	332	11	off	off	NOUN
ijassa-1442	332	12	across	across	ADP
ijassa-1442	332	13	all	all	DET
ijassa-1442	332	14	other	other	ADJ
ijassa-1442	332	15	models	model	NOUN
ijassa-1442	332	16	.	.	PUNCT
ijassa-1442	333	1	as	as	ADP
ijassa-1442	333	2	evident	evident	ADJ
ijassa-1442	333	3	from	from	ADP
ijassa-1442	333	4	table	table	NOUN
ijassa-1442	333	5	7	7	NUM
ijassa-1442	333	6	,	,	PUNCT
ijassa-1442	333	7	in	in	ADP
ijassa-1442	333	8	all	all	DET
ijassa-1442	333	9	cases	case	NOUN
ijassa-1442	333	10	of	of	ADP
ijassa-1442	333	11	trade	trade	NOUN
ijassa-1442	333	12	-	-	PUNCT
ijassa-1442	333	13	offs	off	NOUN
ijassa-1442	333	14	between	between	ADP
ijassa-1442	333	15	,	,	PUNCT
ijassa-1442	333	16	the	the	DET
ijassa-1442	333	17	average	average	ADJ
ijassa-1442	333	18	values	value	NOUN
ijassa-1442	333	19	are	be	AUX
ijassa-1442	333	20	better	well	ADJ
ijassa-1442	333	21	than	than	ADP
ijassa-1442	333	22	those	those	PRON
ijassa-1442	333	23	of	of	ADP
ijassa-1442	333	24	the	the	DET
ijassa-1442	333	25	unfair	unfair	ADJ
ijassa-1442	333	26	solution	solution	NOUN
ijassa-1442	333	27	(	(	PUNCT
ijassa-1442	333	28	with	with	ADP
ijassa-1442	333	29	a	a	DET
ijassa-1442	333	30	difference	difference	NOUN
ijassa-1442	333	31	of	of	ADP
ijassa-1442	333	32	0.4	0.4	NUM
ijassa-1442	333	33	%	%	NOUN
ijassa-1442	333	34	to	to	ADP
ijassa-1442	333	35	1.7	1.7	NUM
ijassa-1442	333	36	%	%	NOUN
ijassa-1442	333	37	)	)	PUNCT
ijassa-1442	333	38	,	,	PUNCT
ijassa-1442	333	39	indicating	indicate	VERB
ijassa-1442	333	40	consistent	consistent	ADJ
ijassa-1442	333	41	improvements	improvement	NOUN
ijassa-1442	333	42	in	in	ADP
ijassa-1442	333	43	terms	term	NOUN
ijassa-1442	333	44	of	of	ADP
ijassa-1442	333	45	this	this	DET
ijassa-1442	333	46	metric	metric	NOUN
ijassa-1442	333	47	.	.	PUNCT
ijassa-1442	334	1	it	it	PRON
ijassa-1442	334	2	is	be	AUX
ijassa-1442	334	3	important	important	ADJ
ijassa-1442	334	4	to	to	PART
ijassa-1442	334	5	note	note	VERB
ijassa-1442	334	6	that	that	SCONJ
ijassa-1442	334	7	the	the	DET
ijassa-1442	334	8	introduction	introduction	NOUN
ijassa-1442	334	9	of	of	ADP
ijassa-1442	334	10	noise	noise	NOUN
ijassa-1442	334	11	increases	increase	VERB
ijassa-1442	334	12	the	the	DET
ijassa-1442	334	13	variability	variability	NOUN
ijassa-1442	334	14	between	between	ADP
ijassa-1442	334	15	the	the	DET
ijassa-1442	334	16	minimum	minimum	ADJ
ijassa-1442	334	17	and	and	CCONJ
ijassa-1442	334	18	maximum	maximum	ADJ
ijassa-1442	334	19	values	value	NOUN
ijassa-1442	334	20	(	(	PUNCT
ijassa-1442	334	21	from	from	ADP
ijassa-1442	334	22	approximately	approximately	ADV
ijassa-1442	334	23	3	3	NUM
ijassa-1442	334	24	%	%	NOUN
ijassa-1442	334	25	for	for	ADP
ijassa-1442	334	26	non	non	ADJ
ijassa-1442	334	27	-	-	ADJ
ijassa-1442	334	28	private	private	ADJ
ijassa-1442	334	29	models	model	NOUN
ijassa-1442	334	30	to	to	ADP
ijassa-1442	334	31	around	around	ADP
ijassa-1442	334	32	10	10	NUM
ijassa-1442	334	33	%	%	NOUN
ijassa-1442	334	34	for	for	ADP
ijassa-1442	334	35	private	private	ADJ
ijassa-1442	334	36	models	model	NOUN
ijassa-1442	334	37	)	)	PUNCT
ijassa-1442	334	38	,	,	PUNCT
ijassa-1442	334	39	but	but	CCONJ
ijassa-1442	334	40	it	it	PRON
ijassa-1442	334	41	also	also	ADV
ijassa-1442	334	42	leads	lead	VERB
ijassa-1442	334	43	to	to	ADP
ijassa-1442	334	44	an	an	DET
ijassa-1442	334	45	increase	increase	NOUN
ijassa-1442	334	46	of	of	ADP
ijassa-1442	334	47	approximately	approximately	ADV
ijassa-1442	334	48	2	2	NUM
ijassa-1442	334	49	-	-	SYM
ijassa-1442	334	50	3	3	NUM
ijassa-1442	334	51	%	%	NOUN
ijassa-1442	334	52	in	in	ADP
ijassa-1442	334	53	the	the	DET
ijassa-1442	334	54	maximum	maximum	ADJ
ijassa-1442	334	55	value	value	NOUN
ijassa-1442	334	56	.	.	PUNCT
ijassa-1442	335	1	there	there	PRON
ijassa-1442	335	2	are	be	VERB
ijassa-1442	335	3	no	no	DET
ijassa-1442	335	4	differences	difference	NOUN
ijassa-1442	335	5	observed	observe	VERB
ijassa-1442	335	6	between	between	ADP
ijassa-1442	335	7	architectures	architecture	NOUN
ijassa-1442	335	8	,	,	PUNCT
ijassa-1442	335	9	but	but	CCONJ
ijassa-1442	335	10	strengthening	strengthen	VERB
ijassa-1442	335	11	the	the	DET
ijassa-1442	335	12	adversary	adversary	NOUN
ijassa-1442	335	13	may	may	AUX
ijassa-1442	335	14	yield	yield	VERB
ijassa-1442	335	15	improvements	improvement	NOUN
ijassa-1442	335	16	of	of	ADP
ijassa-1442	335	17	1	1	NUM
ijassa-1442	335	18	-	-	SYM
ijassa-1442	335	19	2	2	NUM
ijassa-1442	335	20	%	%	NOUN
ijassa-1442	335	21	in	in	ADP
ijassa-1442	335	22	some	some	DET
ijassa-1442	335	23	cases	case	NOUN
ijassa-1442	335	24	.	.	PUNCT
ijassa-1442	336	1	when	when	SCONJ
ijassa-1442	336	2	considering	consider	VERB
ijassa-1442	336	3	,	,	PUNCT
ijassa-1442	336	4	the	the	DET
ijassa-1442	336	5	average	average	ADJ
ijassa-1442	336	6	values	value	NOUN
ijassa-1442	336	7	generally	generally	ADV
ijassa-1442	336	8	fall	fall	VERB
ijassa-1442	336	9	behind	behind	ADP
ijassa-1442	336	10	the	the	DET
ijassa-1442	336	11	unfair	unfair	ADJ
ijassa-1442	336	12	solution	solution	NOUN
ijassa-1442	336	13	by	by	ADP
ijassa-1442	336	14	2	2	NUM
ijassa-1442	336	15	-	-	SYM
ijassa-1442	336	16	6	6	NUM
ijassa-1442	336	17	%	%	NOUN
ijassa-1442	336	18	.	.	PUNCT
ijassa-1442	337	1	however	however	ADV
ijassa-1442	337	2	,	,	PUNCT
ijassa-1442	337	3	in	in	ADP
ijassa-1442	337	4	the	the	DET
ijassa-1442	337	5	maximum	maximum	ADJ
ijassa-1442	337	6	column	column	NOUN
ijassa-1442	337	7	,	,	PUNCT
ijassa-1442	337	8	all	all	DET
ijassa-1442	337	9	values	value	NOUN
ijassa-1442	337	10	are	be	AUX
ijassa-1442	337	11	equal	equal	ADJ
ijassa-1442	337	12	to	to	ADP
ijassa-1442	337	13	or	or	CCONJ
ijassa-1442	337	14	greater	great	ADJ
ijassa-1442	337	15	than	than	ADP
ijassa-1442	337	16	the	the	DET
ijassa-1442	337	17	unfair	unfair	ADJ
ijassa-1442	337	18	solution	solution	NOUN
ijassa-1442	337	19	,	,	PUNCT
ijassa-1442	337	20	indicating	indicate	VERB
ijassa-1442	337	21	the	the	DET
ijassa-1442	337	22	need	need	NOUN
ijassa-1442	337	23	for	for	ADP
ijassa-1442	337	24	more	more	ADV
ijassa-1442	337	25	nuanced	nuanced	ADJ
ijassa-1442	337	26	adjustments	adjustment	NOUN
ijassa-1442	337	27	.	.	PUNCT
ijassa-1442	338	1	on	on	ADP
ijassa-1442	338	2	average	average	ADJ
ijassa-1442	338	3	,	,	PUNCT
ijassa-1442	338	4	laftr	laftr	ADJ
ijassa-1442	338	5	-	-	PUNCT
ijassa-1442	338	6	dp	dp	NOUN
ijassa-1442	338	7	demonstrates	demonstrate	VERB
ijassa-1442	338	8	values	value	NOUN
ijassa-1442	338	9	superior	superior	ADJ
ijassa-1442	338	10	to	to	PART
ijassa-1442	338	11	laftr	laftr	NOUN
ijassa-1442	338	12	-	-	PUNCT
ijassa-1442	338	13	eod	eod	NOUN
ijassa-1442	338	14	by	by	ADP
ijassa-1442	338	15	1	1	NUM
ijassa-1442	338	16	%	%	NOUN
ijassa-1442	338	17	.	.	PUNCT
ijassa-1442	339	1	it	it	PRON
ijassa-1442	339	2	is	be	AUX
ijassa-1442	339	3	worth	worth	ADJ
ijassa-1442	339	4	noting	note	VERB
ijassa-1442	339	5	the	the	DET
ijassa-1442	339	6	high	high	ADJ
ijassa-1442	339	7	stability	stability	NOUN
ijassa-1442	339	8	of	of	ADP
ijassa-1442	339	9	laftr	laftr	NOUN
ijassa-1442	339	10	-	-	PUNCT
ijassa-1442	339	11	dp	dp	NOUN
ijassa-1442	339	12	without	without	ADP
ijassa-1442	339	13	privacy	privacy	NOUN
ijassa-1442	339	14	,	,	PUNCT
ijassa-1442	339	15	with	with	ADP
ijassa-1442	339	16	a	a	DET
ijassa-1442	339	17	variability	variability	NOUN
ijassa-1442	339	18	of	of	ADP
ijassa-1442	339	19	4	4	NUM
ijassa-1442	339	20	%	%	NOUN
ijassa-1442	339	21	and	and	CCONJ
ijassa-1442	339	22	7	7	NUM
ijassa-1442	339	23	%	%	NOUN
ijassa-1442	339	24	between	between	ADP
ijassa-1442	339	25	the	the	DET
ijassa-1442	339	26	minimum	minimum	ADJ
ijassa-1442	339	27	and	and	CCONJ
ijassa-1442	339	28	maximum	maximum	ADJ
ijassa-1442	339	29	values	value	NOUN
ijassa-1442	339	30	for	for	ADP
ijassa-1442	339	31	different	different	ADJ
ijassa-1442	339	32	adversaries	adversary	NOUN
ijassa-1442	339	33	,	,	PUNCT
ijassa-1442	339	34	while	while	SCONJ
ijassa-1442	339	35	the	the	DET
ijassa-1442	339	36	others	other	NOUN
ijassa-1442	339	37	range	range	VERB
ijassa-1442	339	38	from	from	ADP
ijassa-1442	339	39	12	12	NUM
ijassa-1442	339	40	%	%	NOUN
ijassa-1442	339	41	to	to	PART
ijassa-1442	339	42	18	18	NUM
ijassa-1442	339	43	%	%	NOUN
ijassa-1442	339	44	.	.	PUNCT
ijassa-1442	340	1	in	in	ADP
ijassa-1442	340	2	general	general	ADJ
ijassa-1442	340	3	,	,	PUNCT
ijassa-1442	340	4	for	for	ADP
ijassa-1442	340	5	this	this	DET
ijassa-1442	340	6	dataset	dataset	NOUN
ijassa-1442	340	7	,	,	PUNCT
ijassa-1442	340	8	it	it	PRON
ijassa-1442	340	9	can	can	AUX
ijassa-1442	340	10	be	be	AUX
ijassa-1442	340	11	stated	state	VERB
ijassa-1442	340	12	that	that	SCONJ
ijassa-1442	340	13	with	with	ADP
ijassa-1442	340	14	proper	proper	ADJ
ijassa-1442	340	15	configuration	configuration	NOUN
ijassa-1442	340	16	,	,	PUNCT
ijassa-1442	340	17	outstanding	outstanding	ADJ
ijassa-1442	340	18	fairness	fairness	NOUN
ijassa-1442	340	19	results	result	NOUN
ijassa-1442	340	20	can	can	AUX
ijassa-1442	340	21	be	be	AUX
ijassa-1442	340	22	achieved	achieve	VERB
ijassa-1442	340	23	while	while	SCONJ
ijassa-1442	340	24	sacrificing	sacrifice	VERB
ijassa-1442	340	25	less	less	ADV
ijassa-1442	340	26	in	in	ADP
ijassa-1442	340	27	terms	term	NOUN
ijassa-1442	340	28	of	of	ADP
ijassa-1442	340	29	accuracy	accuracy	NOUN
ijassa-1442	340	30	compared	compare	VERB
ijassa-1442	340	31	to	to	ADP
ijassa-1442	340	32	gains	gain	NOUN
ijassa-1442	340	33	in	in	ADP
ijassa-1442	340	34	any	any	DET
ijassa-1442	340	35	fairness	fairness	NOUN
ijassa-1442	340	36	metric	metric	NOUN
ijassa-1442	340	37	.	.	PUNCT
ijassa-1442	341	1	furthermore	furthermore	ADV
ijassa-1442	341	2	,	,	PUNCT
ijassa-1442	341	3	based	base	VERB
ijassa-1442	341	4	on	on	ADP
ijassa-1442	341	5	all	all	DET
ijassa-1442	341	6	the	the	DET
ijassa-1442	341	7	results	result	NOUN
ijassa-1442	341	8	,	,	PUNCT
ijassa-1442	341	9	it	it	PRON
ijassa-1442	341	10	becomes	become	VERB
ijassa-1442	341	11	evident	evident	ADJ
ijassa-1442	341	12	that	that	SCONJ
ijassa-1442	341	13	strengthening	strengthen	VERB
ijassa-1442	341	14	the	the	DET
ijassa-1442	341	15	adversary	adversary	NOUN
ijassa-1442	341	16	has	have	VERB
ijassa-1442	341	17	a	a	DET
ijassa-1442	341	18	positive	positive	ADJ
ijassa-1442	341	19	impact	impact	NOUN
ijassa-1442	341	20	on	on	ADP
ijassa-1442	341	21	the	the	DET
ijassa-1442	341	22	trade	trade	NOUN
ijassa-1442	341	23	-	-	PUNCT
ijassa-1442	341	24	off	off	NOUN
ijassa-1442	341	25	,	,	PUNCT
ijassa-1442	341	26	but	but	CCONJ
ijassa-1442	341	27	only	only	ADV
ijassa-1442	341	28	when	when	SCONJ
ijassa-1442	341	29	carefully	carefully	ADV
ijassa-1442	341	30	fine	fine	ADV
ijassa-1442	341	31	-	-	PUNCT
ijassa-1442	341	32	tuned	tune	VERB
ijassa-1442	341	33	;	;	PUNCT
ijassa-1442	341	34	otherwise	otherwise	ADV
ijassa-1442	341	35	,	,	PUNCT
ijassa-1442	341	36	it	it	PRON
ijassa-1442	341	37	may	may	AUX
ijassa-1442	341	38	lead	lead	VERB
ijassa-1442	341	39	to	to	ADP
ijassa-1442	341	40	poor	poor	ADJ
ijassa-1442	341	41	outcomes	outcome	NOUN
ijassa-1442	341	42	.	.	PUNCT
ijassa-1442	342	1	additionally	additionally	ADV
ijassa-1442	342	2	,	,	PUNCT
ijassa-1442	342	3	it	it	PRON
ijassa-1442	342	4	is	be	AUX
ijassa-1442	342	5	not	not	PART
ijassa-1442	342	6	possible	possible	ADJ
ijassa-1442	342	7	to	to	PART
ijassa-1442	342	8	confidently	confidently	ADV
ijassa-1442	342	9	assert	assert	VERB
ijassa-1442	342	10	that	that	DET
ijassa-1442	342	11	laftr	laftr	ADJ
ijassa-1442	342	12	-	-	PUNCT
ijassa-1442	342	13	dp	dp	NOUN
ijassa-1442	342	14	outperforms	outperform	NOUN
ijassa-1442	342	15	laftr	laftr	NOUN
ijassa-1442	342	16	-	-	PUNCT
ijassa-1442	342	17	eod	eod	NOUN
ijassa-1442	342	18	,	,	PUNCT
ijassa-1442	342	19	as	as	SCONJ
ijassa-1442	342	20	it	it	PRON
ijassa-1442	342	21	depends	depend	VERB
ijassa-1442	342	22	on	on	ADP
ijassa-1442	342	23	the	the	DET
ijassa-1442	342	24	specific	specific	ADJ
ijassa-1442	342	25	task	task	NOUN
ijassa-1442	342	26	,	,	PUNCT
ijassa-1442	342	27	where	where	SCONJ
ijassa-1442	342	28	laftr	laftr	NOUN
ijassa-1442	342	29	-	-	PUNCT
ijassa-1442	342	30	eod	eod	NOUN
ijassa-1442	342	31	may	may	AUX
ijassa-1442	342	32	perform	perform	VERB
ijassa-1442	342	33	better	well	ADV
ijassa-1442	342	34	in	in	ADP
ijassa-1442	342	35	certain	certain	ADJ
ijassa-1442	342	36	cases	case	NOUN
ijassa-1442	342	37	.	.	PUNCT
ijassa-1442	343	1	finally	finally	ADV
ijassa-1442	343	2	,	,	PUNCT
ijassa-1442	343	3	it	it	PRON
ijassa-1442	343	4	can	can	AUX
ijassa-1442	343	5	be	be	AUX
ijassa-1442	343	6	concluded	conclude	VERB
ijassa-1442	343	7	that	that	SCONJ
ijassa-1442	343	8	by	by	ADP
ijassa-1442	343	9	incorporating	incorporate	VERB
ijassa-1442	343	10	privacy	privacy	NOUN
ijassa-1442	343	11	at	at	ADP
ijassa-1442	343	12	various	various	ADJ
ijassa-1442	343	13	levels	level	NOUN
ijassa-1442	343	14	,	,	PUNCT
ijassa-1442	343	15	it	it	PRON
ijassa-1442	343	16	is	be	AUX
ijassa-1442	343	17	feasible	feasible	ADJ
ijassa-1442	343	18	to	to	PART
ijassa-1442	343	19	attain	attain	VERB
ijassa-1442	343	20	either	either	CCONJ
ijassa-1442	343	21	a	a	DET
ijassa-1442	343	22	highly	highly	ADV
ijassa-1442	343	23	fair	fair	ADJ
ijassa-1442	343	24	model	model	NOUN
ijassa-1442	343	25	or	or	CCONJ
ijassa-1442	343	26	avoid	avoid	VERB
ijassa-1442	343	27	significant	significant	ADJ
ijassa-1442	343	28	accuracy	accuracy	NOUN
ijassa-1442	343	29	losses	loss	NOUN
ijassa-1442	343	30	while	while	SCONJ
ijassa-1442	343	31	improving	improve	VERB
ijassa-1442	343	32	fairness	fairness	NOUN
ijassa-1442	343	33	.	.	PUNCT
ijassa-1442	344	1	balancing	balance	VERB
ijassa-1442	344	2	accuracy	accuracy	NOUN
ijassa-1442	344	3	,	,	PUNCT
ijassa-1442	344	4	fairness	fairness	NOUN
ijassa-1442	344	5	and	and	CCONJ
ijassa-1442	344	6	privacy	privacy	NOUN
ijassa-1442	344	7	in	in	ADP
ijassa-1442	344	8	machine	machine	NOUN
ijassa-1442	344	9	learning	learning	NOUN
ijassa-1442	344	10	…	…	PUNCT
ijassa-1442	344	11	55	55	NUM
ijassa-1442	344	12	copyright	copyright	NOUN
ijassa-1442	344	13	©	©	PROPN
ijassa-1442	344	14	2023	2023	NUM
ijassa-1442	344	15	assa	assa	NOUN
ijassa-1442	344	16	.	.	PUNCT
ijassa-1442	345	1	adv	adv	PROPN
ijassa-1442	345	2	.	.	PUNCT
ijassa-1442	346	1	in	in	ADP
ijassa-1442	346	2	systems	system	NOUN
ijassa-1442	346	3	science	science	NOUN
ijassa-1442	346	4	and	and	CCONJ
ijassa-1442	346	5	appl	appl	NOUN
ijassa-1442	346	6	.	.	PUNCT
ijassa-1442	347	1	(	(	PUNCT
ijassa-1442	347	2	2023	2023	NUM
ijassa-1442	347	3	)	)	PUNCT
ijassa-1442	347	4	fig	fig	NOUN
ijassa-1442	347	5	.	.	PUNCT
ijassa-1442	348	1	5	5	NUM
ijassa-1442	348	2	dependence	dependence	NOUN
ijassa-1442	348	3	of	of	ADP
ijassa-1442	348	4	acc	acc	PROPN
ijassa-1442	348	5	/	/	SYM
ijassa-1442	348	6	fair	fair	ADJ
ijassa-1442	348	7	on	on	ADP
ijassa-1442	348	8	for	for	ADP
ijassa-1442	348	9	adult	adult	NOUN
ijassa-1442	348	10	dataset	dataset	NOUN
ijassa-1442	348	11	56	56	NUM
ijassa-1442	348	12	a.	a.	NOUN
ijassa-1442	348	13	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	348	14	,	,	PUNCT
ijassa-1442	348	15	r.	r.	PROPN
ijassa-1442	348	16	sabitov	sabitov	PROPN
ijassa-1442	348	17	,	,	PUNCT
ijassa-1442	348	18	g.	g.	PROPN
ijassa-1442	348	19	smirnova	smirnova	PROPN
ijassa-1442	348	20	,	,	PUNCT
ijassa-1442	348	21	sh	sh	PROPN
ijassa-1442	348	22	.	.	PUNCT
ijassa-1442	348	23	sabitov	sabitov	PROPN
ijassa-1442	348	24	copyright	copyright	NOUN
ijassa-1442	348	25	©	©	PROPN
ijassa-1442	348	26	2023	2023	NUM
ijassa-1442	348	27	assa	assa	PROPN
ijassa-1442	348	28	adv	adv	PROPN
ijassa-1442	348	29	.	.	PUNCT
ijassa-1442	349	1	in	in	ADP
ijassa-1442	349	2	systems	system	NOUN
ijassa-1442	349	3	science	science	NOUN
ijassa-1442	349	4	and	and	CCONJ
ijassa-1442	349	5	appl	appl	NOUN
ijassa-1442	349	6	.	.	PUNCT
ijassa-1442	350	1	(	(	PUNCT
ijassa-1442	350	2	2023	2023	NUM
ijassa-1442	350	3	)	)	PUNCT
ijassa-1442	350	4	fig	fig	NOUN
ijassa-1442	350	5	.	.	PUNCT
ijassa-1442	351	1	6	6	NUM
ijassa-1442	351	2	dependence	dependence	NOUN
ijassa-1442	351	3	of	of	ADP
ijassa-1442	351	4	acc	acc	PROPN
ijassa-1442	351	5	/	/	SYM
ijassa-1442	351	6	fair	fair	ADJ
ijassa-1442	351	7	on	on	ADP
ijassa-1442	351	8	for	for	ADP
ijassa-1442	351	9	adult	adult	NOUN
ijassa-1442	351	10	dataset	dataset	NOUN
ijassa-1442	351	11	table	table	NOUN
ijassa-1442	351	12	7	7	NUM
ijassa-1442	351	13	general	general	ADJ
ijassa-1442	351	14	accuracy	accuracy	NOUN
ijassa-1442	351	15	-	-	PUNCT
ijassa-1442	351	16	fairness	fairness	NOUN
ijassa-1442	351	17	trade	trade	NOUN
ijassa-1442	351	18	-	-	PUNCT
ijassa-1442	351	19	off	off	ADP
ijassa-1442	351	20	comparison	comparison	NOUN
ijassa-1442	351	21	.	.	PUNCT
ijassa-1442	352	1	adult	adult	NOUN
ijassa-1442	352	2	dataset	dataset	NOUN
ijassa-1442	352	3	.	.	PUNCT
ijassa-1442	353	1	acc	acc	PROPN
ijassa-1442	353	2	/	/	SYM
ijassa-1442	353	3	fair	fair	ADJ
ijassa-1442	353	4	δdp	δdp	NOUN
ijassa-1442	353	5	model	model	NOUN
ijassa-1442	353	6	privacy	privacy	NOUN
ijassa-1442	353	7	adversary	adversary	NOUN
ijassa-1442	353	8	min	min	PROPN
ijassa-1442	353	9	max	max	PROPN
ijassa-1442	353	10	mean	mean	VERB
ijassa-1442	353	11	laftr	laftr	ADV
ijassa-1442	353	12	-	-	PUNCT
ijassa-1442	353	13	dp	dp	NOUN
ijassa-1442	353	14	no	no	DET
ijassa-1442	353	15	privacy	privacy	NOUN
ijassa-1442	353	16	adversary	adversary	NOUN
ijassa-1442	353	17	=	=	SYM
ijassa-1442	353	18	classifier	classifier	NOUN
ijassa-1442	353	19	0.716	0.716	NUM
ijassa-1442	353	20	0.755	0.755	NUM
ijassa-1442	353	21	0.739	0.739	NUM
ijassa-1442	353	22	adversary	adversary	NOUN
ijassa-1442	353	23	>	>	X
ijassa-1442	353	24	classifier	classifier	NOUN
ijassa-1442	353	25	0.723	0.723	NUM
ijassa-1442	353	26	0.761	0.761	NUM
ijassa-1442	353	27	0.747	0.747	NUM
ijassa-1442	353	28	privacy	privacy	NOUN
ijassa-1442	353	29	in	in	ADP
ijassa-1442	353	30	..	..	PUNCT
ijassa-1442	353	31	adversary	adversary	NOUN
ijassa-1442	353	32	=	=	NOUN
ijassa-1442	353	33	classifier	classifier	NOUN
ijassa-1442	353	34	0.683	0.683	NUM
ijassa-1442	353	35	0.789	0.789	NUM
ijassa-1442	353	36	0.734	0.734	NUM
ijassa-1442	353	37	adversary	adversary	NOUN
ijassa-1442	353	38	>	>	X
ijassa-1442	353	39	classifier	classifier	NOUN
ijassa-1442	353	40	0.694	0.694	NUM
ijassa-1442	353	41	0.783	0.783	NUM
ijassa-1442	353	42	0.735	0.735	NUM
ijassa-1442	353	43	laftr	laftr	ADJ
ijassa-1442	353	44	-	-	PUNCT
ijassa-1442	353	45	eod	eod	NOUN
ijassa-1442	353	46	no	no	DET
ijassa-1442	353	47	privacy	privacy	NOUN
ijassa-1442	353	48	adversary	adversary	NOUN
ijassa-1442	353	49	=	=	SYM
ijassa-1442	353	50	classifier	classifier	NOUN
ijassa-1442	353	51	0.716	0.716	NUM
ijassa-1442	353	52	0.766	0.766	NUM
ijassa-1442	353	53	0.744	0.744	NUM
ijassa-1442	353	54	adversary	adversary	NOUN
ijassa-1442	353	55	>	>	X
ijassa-1442	353	56	classifier	classifier	NOUN
ijassa-1442	353	57	0.720	0.720	NUM
ijassa-1442	353	58	0.766	0.766	NUM
ijassa-1442	353	59	0.744	0.744	NUM
ijassa-1442	353	60	privacy	privacy	NOUN
ijassa-1442	353	61	in	in	ADP
ijassa-1442	353	62	..	..	PUNCT
ijassa-1442	353	63	adversary	adversary	NOUN
ijassa-1442	353	64	=	=	SYM
ijassa-1442	353	65	classifier	classifier	NOUN
ijassa-1442	353	66	0.678	0.678	NUM
ijassa-1442	353	67	0.779	0.779	NUM
ijassa-1442	353	68	0.734	0.734	NUM
ijassa-1442	353	69	adversary	adversary	NOUN
ijassa-1442	353	70	>	>	X
ijassa-1442	353	71	classifier	classifier	NOUN
ijassa-1442	353	72	0.698	0.698	NUM
ijassa-1442	353	73	0.777	0.777	NUM
ijassa-1442	353	74	0.737	0.737	NUM
ijassa-1442	353	75	unfair	unfair	ADJ
ijassa-1442	353	76	no	no	DET
ijassa-1442	353	77	privacy	privacy	NOUN
ijassa-1442	353	78	0.730	0.730	NUM
ijassa-1442	353	79	0.730	0.730	NUM
ijassa-1442	353	80	0.730	0.730	NUM
ijassa-1442	353	81	acc	acc	PROPN
ijassa-1442	353	82	/	/	SYM
ijassa-1442	353	83	fair	fair	ADJ
ijassa-1442	353	84	δeod	δeod	NOUN
ijassa-1442	353	85	model	model	NOUN
ijassa-1442	353	86	privacy	privacy	NOUN
ijassa-1442	353	87	adversary	adversary	NOUN
ijassa-1442	353	88	min	min	PROPN
ijassa-1442	353	89	max	max	PROPN
ijassa-1442	353	90	mean	mean	VERB
ijassa-1442	353	91	laftr	laftr	ADV
ijassa-1442	353	92	-	-	PUNCT
ijassa-1442	353	93	dp	dp	NOUN
ijassa-1442	353	94	no	no	DET
ijassa-1442	353	95	privacy	privacy	NOUN
ijassa-1442	353	96	adversary	adversary	NOUN
ijassa-1442	353	97	=	=	SYM
ijassa-1442	353	98	classifier	classifier	NOUN
ijassa-1442	353	99	0.723	0.723	NUM
ijassa-1442	353	100	0.764	0.764	NUM
ijassa-1442	353	101	0.747	0.747	NUM
ijassa-1442	353	102	adversary	adversary	NOUN
ijassa-1442	353	103	>	>	X
ijassa-1442	353	104	classifier	classifier	NOUN
ijassa-1442	353	105	0.694	0.694	NUM
ijassa-1442	353	106	0.776	0.776	NUM
ijassa-1442	353	107	0.737	0.737	NUM
ijassa-1442	353	108	privacy	privacy	NOUN
ijassa-1442	353	109	in	in	ADP
ijassa-1442	353	110	..	..	PUNCT
ijassa-1442	353	111	adversary	adversary	NOUN
ijassa-1442	353	112	=	=	NOUN
ijassa-1442	353	113	classifier	classifier	NOUN
ijassa-1442	353	114	0.595	0.595	NUM
ijassa-1442	353	115	0.773	0.773	NUM
ijassa-1442	353	116	0.707	0.707	NUM
ijassa-1442	353	117	adversary	adversary	NOUN
ijassa-1442	353	118	>	>	X
ijassa-1442	353	119	classifier	classifier	NOUN
ijassa-1442	353	120	0.604	0.604	NUM
ijassa-1442	353	121	0.763	0.763	NUM
ijassa-1442	353	122	0.714	0.714	NUM
ijassa-1442	353	123	laftr	laftr	ADJ
ijassa-1442	353	124	-	-	PUNCT
ijassa-1442	353	125	eod	eod	NOUN
ijassa-1442	353	126	no	no	DET
ijassa-1442	353	127	privacy	privacy	NOUN
ijassa-1442	353	128	adversary	adversary	NOUN
ijassa-1442	353	129	=	=	SYM
ijassa-1442	353	130	classifier	classifier	NOUN
ijassa-1442	353	131	0.687	0.687	NUM
ijassa-1442	353	132	0.769	0.769	NUM
ijassa-1442	353	133	0.722	0.722	NUM
ijassa-1442	353	134	balancing	balancing	NOUN
ijassa-1442	353	135	accuracy	accuracy	NOUN
ijassa-1442	353	136	,	,	PUNCT
ijassa-1442	353	137	fairness	fairness	NOUN
ijassa-1442	353	138	and	and	CCONJ
ijassa-1442	353	139	privacy	privacy	NOUN
ijassa-1442	353	140	in	in	ADP
ijassa-1442	353	141	machine	machine	NOUN
ijassa-1442	353	142	learning	learning	NOUN
ijassa-1442	353	143	…	…	PUNCT
ijassa-1442	353	144	57	57	NUM
ijassa-1442	353	145	copyright	copyright	NOUN
ijassa-1442	353	146	©	©	PROPN
ijassa-1442	353	147	2023	2023	NUM
ijassa-1442	353	148	assa	assa	NOUN
ijassa-1442	353	149	.	.	PUNCT
ijassa-1442	354	1	adv	adv	PROPN
ijassa-1442	354	2	.	.	PUNCT
ijassa-1442	355	1	in	in	ADP
ijassa-1442	355	2	systems	system	NOUN
ijassa-1442	355	3	science	science	NOUN
ijassa-1442	355	4	and	and	CCONJ
ijassa-1442	355	5	appl	appl	NOUN
ijassa-1442	355	6	.	.	PUNCT
ijassa-1442	356	1	(	(	PUNCT
ijassa-1442	356	2	2023	2023	NUM
ijassa-1442	356	3	)	)	PUNCT
ijassa-1442	356	4	adversary	adversary	NOUN
ijassa-1442	356	5	>	>	X
ijassa-1442	356	6	classifier	classifier	NOUN
ijassa-1442	356	7	0.668	0.668	SYM
ijassa-1442	356	8	0.785	0.785	NUM
ijassa-1442	356	9	0.728	0.728	NUM
ijassa-1442	356	10	privacy	privacy	NOUN
ijassa-1442	356	11	in	in	ADP
ijassa-1442	356	12	..	..	PUNCT
ijassa-1442	356	13	adversary	adversary	NOUN
ijassa-1442	356	14	=	=	NOUN
ijassa-1442	356	15	classifier	classifier	NOUN
ijassa-1442	356	16	0.594	0.594	NUM
ijassa-1442	356	17	0.776	0.776	NUM
ijassa-1442	356	18	0.702	0.702	NUM
ijassa-1442	356	19	adversary	adversary	NOUN
ijassa-1442	356	20	>	>	X
ijassa-1442	356	21	classifier	classifier	NOUN
ijassa-1442	356	22	0.624	0.624	NUM
ijassa-1442	356	23	0.774	0.774	NUM
ijassa-1442	356	24	0.716	0.716	NUM
ijassa-1442	356	25	unfair	unfair	ADJ
ijassa-1442	356	26	no	no	DET
ijassa-1442	356	27	privacy	privacy	NOUN
ijassa-1442	356	28	0.764	0.764	NUM
ijassa-1442	356	29	0.764	0.764	NUM
ijassa-1442	356	30	0.764	0.764	NUM
ijassa-1442	356	31	6	6	NUM
ijassa-1442	356	32	.	.	PUNCT
ijassa-1442	357	1	conclusion	conclusion	NOUN
ijassa-1442	357	2	this	this	DET
ijassa-1442	357	3	research	research	NOUN
ijassa-1442	357	4	study	study	NOUN
ijassa-1442	357	5	aimed	aim	VERB
ijassa-1442	357	6	to	to	PART
ijassa-1442	357	7	develop	develop	VERB
ijassa-1442	357	8	a	a	DET
ijassa-1442	357	9	benchmark	benchmark	NOUN
ijassa-1442	357	10	to	to	PART
ijassa-1442	357	11	evaluate	evaluate	VERB
ijassa-1442	357	12	differentially	differentially	ADV
ijassa-1442	357	13	private	private	ADJ
ijassa-1442	357	14	fair	fair	ADJ
ijassa-1442	357	15	representations	representation	NOUN
ijassa-1442	357	16	across	across	ADP
ijassa-1442	357	17	various	various	ADJ
ijassa-1442	357	18	model	model	NOUN
ijassa-1442	357	19	configurations	configuration	NOUN
ijassa-1442	357	20	and	and	CCONJ
ijassa-1442	357	21	datasets	dataset	NOUN
ijassa-1442	357	22	and	and	CCONJ
ijassa-1442	357	23	research	research	NOUN
ijassa-1442	357	24	results	result	NOUN
ijassa-1442	357	25	.	.	PUNCT
ijassa-1442	358	1	the	the	DET
ijassa-1442	358	2	following	follow	VERB
ijassa-1442	358	3	key	key	ADJ
ijassa-1442	358	4	findings	finding	NOUN
ijassa-1442	358	5	were	be	AUX
ijassa-1442	358	6	obtained	obtain	VERB
ijassa-1442	358	7	during	during	ADP
ijassa-1442	358	8	the	the	DET
ijassa-1442	358	9	study	study	NOUN
ijassa-1442	358	10	:	:	PUNCT
ijassa-1442	358	11			ADJ
ijassa-1442	358	12	firstly	firstly	ADV
ijassa-1442	358	13	,	,	PUNCT
ijassa-1442	358	14	the	the	DET
ijassa-1442	358	15	impact	impact	NOUN
ijassa-1442	358	16	of	of	ADP
ijassa-1442	358	17	privacy	privacy	NOUN
ijassa-1442	358	18	integration	integration	NOUN
ijassa-1442	358	19	on	on	ADP
ijassa-1442	358	20	fairness	fairness	NOUN
ijassa-1442	358	21	in	in	ADP
ijassa-1442	358	22	the	the	DET
ijassa-1442	358	23	encoding	encoding	NOUN
ijassa-1442	358	24	process	process	NOUN
ijassa-1442	358	25	was	be	AUX
ijassa-1442	358	26	examined	examine	VERB
ijassa-1442	358	27	.	.	PUNCT
ijassa-1442	359	1	it	it	PRON
ijassa-1442	359	2	was	be	AUX
ijassa-1442	359	3	demonstrated	demonstrate	VERB
ijassa-1442	359	4	that	that	SCONJ
ijassa-1442	359	5	with	with	ADP
ijassa-1442	359	6	successful	successful	ADJ
ijassa-1442	359	7	weight	weight	NOUN
ijassa-1442	359	8	initialization	initialization	NOUN
ijassa-1442	359	9	,	,	PUNCT
ijassa-1442	359	10	any	any	DET
ijassa-1442	359	11	model	model	NOUN
ijassa-1442	359	12	could	could	AUX
ijassa-1442	359	13	generate	generate	VERB
ijassa-1442	359	14	nearly	nearly	ADV
ijassa-1442	359	15	fair	fair	ADJ
ijassa-1442	359	16	representations	representation	NOUN
ijassa-1442	359	17	.	.	PUNCT
ijassa-1442	360	1	additionally	additionally	ADV
ijassa-1442	360	2	,	,	PUNCT
ijassa-1442	360	3	statistical	statistical	ADJ
ijassa-1442	360	4	tests	test	NOUN
ijassa-1442	360	5	confirmed	confirm	VERB
ijassa-1442	360	6	the	the	DET
ijassa-1442	360	7	equality	equality	NOUN
ijassa-1442	360	8	of	of	ADP
ijassa-1442	360	9	privacy	privacy	NOUN
ijassa-1442	360	10	-	-	PUNCT
ijassa-1442	360	11	enabled	enable	VERB
ijassa-1442	360	12	models	model	NOUN
ijassa-1442	360	13	in	in	ADP
ijassa-1442	360	14	all	all	DET
ijassa-1442	360	15	cases	case	NOUN
ijassa-1442	360	16	.	.	PUNCT
ijassa-1442	361	1	the	the	DET
ijassa-1442	361	2	level	level	NOUN
ijassa-1442	361	3	of	of	ADP
ijassa-1442	361	4	noise	noise	NOUN
ijassa-1442	361	5	,	,	PUNCT
ijassa-1442	361	6	as	as	ADV
ijassa-1442	361	7	well	well	ADV
ijassa-1442	361	8	as	as	ADP
ijassa-1442	361	9	the	the	DET
ijassa-1442	361	10	number	number	NOUN
ijassa-1442	361	11	of	of	ADP
ijassa-1442	361	12	parts	part	NOUN
ijassa-1442	361	13	it	it	PRON
ijassa-1442	361	14	is	be	AUX
ijassa-1442	361	15	injected	inject	VERB
ijassa-1442	361	16	into	into	ADP
ijassa-1442	361	17	,	,	PUNCT
ijassa-1442	361	18	did	do	AUX
ijassa-1442	361	19	not	not	PART
ijassa-1442	361	20	affect	affect	VERB
ijassa-1442	361	21	the	the	DET
ijassa-1442	361	22	fairness	fairness	NOUN
ijassa-1442	361	23	outcome	outcome	NOUN
ijassa-1442	361	24	.	.	PUNCT
ijassa-1442	362	1	the	the	DET
ijassa-1442	362	2	introduction	introduction	NOUN
ijassa-1442	362	3	of	of	ADP
ijassa-1442	362	4	privacy	privacy	NOUN
ijassa-1442	362	5	improved	improved	ADJ
ijassa-1442	362	6	fairness	fairness	NOUN
ijassa-1442	362	7	by	by	ADP
ijassa-1442	362	8	up	up	ADP
ijassa-1442	362	9	to	to	PART
ijassa-1442	362	10	5	5	NUM
ijassa-1442	362	11	%	%	NOUN
ijassa-1442	362	12	.	.	PUNCT
ijassa-1442	363	1			PUNCT
ijassa-1442	363	2	secondly	secondly	ADV
ijassa-1442	363	3	,	,	PUNCT
ijassa-1442	363	4	it	it	PRON
ijassa-1442	363	5	was	be	AUX
ijassa-1442	363	6	observed	observe	VERB
ijassa-1442	363	7	that	that	SCONJ
ijassa-1442	363	8	privacy	privacy	NOUN
ijassa-1442	363	9	integration	integration	NOUN
ijassa-1442	363	10	had	have	VERB
ijassa-1442	363	11	a	a	DET
ijassa-1442	363	12	negative	negative	ADJ
ijassa-1442	363	13	impact	impact	NOUN
ijassa-1442	363	14	on	on	ADP
ijassa-1442	363	15	model	model	NOUN
ijassa-1442	363	16	accuracy	accuracy	NOUN
ijassa-1442	363	17	,	,	PUNCT
ijassa-1442	363	18	with	with	ADP
ijassa-1442	363	19	a	a	DET
ijassa-1442	363	20	typical	typical	ADJ
ijassa-1442	363	21	decline	decline	NOUN
ijassa-1442	363	22	of	of	ADP
ijassa-1442	363	23	1	1	NUM
ijassa-1442	363	24	-	-	SYM
ijassa-1442	363	25	3	3	NUM
ijassa-1442	363	26	%	%	NOUN
ijassa-1442	363	27	compared	compare	VERB
ijassa-1442	363	28	to	to	ADP
ijassa-1442	363	29	unprotected	unprotected	ADJ
ijassa-1442	363	30	counterparts	counterpart	NOUN
ijassa-1442	363	31	.	.	PUNCT
ijassa-1442	364	1			X
ijassa-1442	365	1	furthermore	furthermore	ADV
ijassa-1442	365	2	,	,	PUNCT
ijassa-1442	365	3	the	the	DET
ijassa-1442	365	4	analysis	analysis	NOUN
ijassa-1442	365	5	of	of	ADP
ijassa-1442	365	6	results	result	NOUN
ijassa-1442	365	7	revealed	reveal	VERB
ijassa-1442	365	8	a	a	DET
ijassa-1442	365	9	pattern	pattern	NOUN
ijassa-1442	365	10	where	where	SCONJ
ijassa-1442	365	11	strengthening	strengthen	VERB
ijassa-1442	365	12	the	the	DET
ijassa-1442	365	13	adversary	adversary	NOUN
ijassa-1442	365	14	could	could	AUX
ijassa-1442	365	15	have	have	AUX
ijassa-1442	365	16	a	a	DET
ijassa-1442	365	17	positive	positive	ADJ
ijassa-1442	365	18	effect	effect	NOUN
ijassa-1442	365	19	on	on	ADP
ijassa-1442	365	20	the	the	DET
ijassa-1442	365	21	outcomes	outcome	NOUN
ijassa-1442	365	22	.	.	PUNCT
ijassa-1442	366	1	however	however	ADV
ijassa-1442	366	2	,	,	PUNCT
ijassa-1442	366	3	careful	careful	ADJ
ijassa-1442	366	4	fine	fine	ADV
ijassa-1442	366	5	-	-	PUNCT
ijassa-1442	366	6	tuning	tuning	NOUN
ijassa-1442	366	7	and	and	CCONJ
ijassa-1442	366	8	monitoring	monitoring	NOUN
ijassa-1442	366	9	of	of	ADP
ijassa-1442	366	10	the	the	DET
ijassa-1442	366	11	training	training	NOUN
ijassa-1442	366	12	process	process	NOUN
ijassa-1442	366	13	were	be	AUX
ijassa-1442	366	14	necessary	necessary	ADJ
ijassa-1442	366	15	due	due	ADP
ijassa-1442	366	16	to	to	ADP
ijassa-1442	366	17	increased	increase	VERB
ijassa-1442	366	18	instability	instability	NOUN
ijassa-1442	366	19	.	.	PUNCT
ijassa-1442	367	1			X
ijassa-1442	368	1	moreover	moreover	ADV
ijassa-1442	368	2	,	,	PUNCT
ijassa-1442	368	3	it	it	PRON
ijassa-1442	368	4	was	be	AUX
ijassa-1442	368	5	shown	show	VERB
ijassa-1442	368	6	that	that	SCONJ
ijassa-1442	368	7	any	any	DET
ijassa-1442	368	8	private	private	ADJ
ijassa-1442	368	9	fair	fair	ADJ
ijassa-1442	368	10	models	model	NOUN
ijassa-1442	368	11	could	could	AUX
ijassa-1442	368	12	achieve	achieve	VERB
ijassa-1442	368	13	up	up	ADP
ijassa-1442	368	14	to	to	PART
ijassa-1442	368	15	5	5	NUM
ijassa-1442	368	16	%	%	NOUN
ijassa-1442	368	17	advantage	advantage	NOUN
ijassa-1442	368	18	in	in	ADP
ijassa-1442	368	19	the	the	DET
ijassa-1442	368	20	compromise	compromise	NOUN
ijassa-1442	368	21	between	between	ADP
ijassa-1442	368	22	accuracy	accuracy	NOUN
ijassa-1442	368	23	and	and	CCONJ
ijassa-1442	368	24	fairness	fairness	NOUN
ijassa-1442	368	25	compared	compare	VERB
ijassa-1442	368	26	to	to	ADP
ijassa-1442	368	27	the	the	DET
ijassa-1442	368	28	"	"	PUNCT
ijassa-1442	368	29	unfair	unfair	ADJ
ijassa-1442	368	30	"	"	PUNCT
ijassa-1442	368	31	model	model	NOUN
ijassa-1442	368	32	.	.	PUNCT
ijassa-1442	369	1	based	base	VERB
ijassa-1442	369	2	on	on	ADP
ijassa-1442	369	3	the	the	DET
ijassa-1442	369	4	study	study	NOUN
ijassa-1442	369	5	's	's	PART
ijassa-1442	369	6	findings	finding	NOUN
ijassa-1442	369	7	,	,	PUNCT
ijassa-1442	369	8	it	it	PRON
ijassa-1442	369	9	can	can	AUX
ijassa-1442	369	10	be	be	AUX
ijassa-1442	369	11	concluded	conclude	VERB
ijassa-1442	369	12	that	that	SCONJ
ijassa-1442	369	13	it	it	PRON
ijassa-1442	369	14	is	be	AUX
ijassa-1442	369	15	possible	possible	ADJ
ijassa-1442	369	16	to	to	PART
ijassa-1442	369	17	train	train	VERB
ijassa-1442	369	18	a	a	DET
ijassa-1442	369	19	fair	fair	ADJ
ijassa-1442	369	20	and	and	CCONJ
ijassa-1442	369	21	private	private	ADJ
ijassa-1442	369	22	model	model	NOUN
ijassa-1442	369	23	with	with	ADP
ijassa-1442	369	24	acceptable	acceptable	ADJ
ijassa-1442	369	25	accuracy	accuracy	NOUN
ijassa-1442	369	26	and	and	CCONJ
ijassa-1442	369	27	a	a	DET
ijassa-1442	369	28	high	high	ADJ
ijassa-1442	369	29	level	level	NOUN
ijassa-1442	369	30	of	of	ADP
ijassa-1442	369	31	protection	protection	NOUN
ijassa-1442	369	32	.	.	PUNCT
ijassa-1442	370	1	however	however	ADV
ijassa-1442	370	2	,	,	PUNCT
ijassa-1442	370	3	achieving	achieve	VERB
ijassa-1442	370	4	such	such	ADJ
ijassa-1442	370	5	results	result	NOUN
ijassa-1442	370	6	requires	require	VERB
ijassa-1442	370	7	fine	fine	ADV
ijassa-1442	370	8	-	-	PUNCT
ijassa-1442	370	9	tuning	tuning	NOUN
ijassa-1442	370	10	or	or	CCONJ
ijassa-1442	370	11	fortunate	fortunate	ADJ
ijassa-1442	370	12	circumstances	circumstance	NOUN
ijassa-1442	370	13	,	,	PUNCT
ijassa-1442	370	14	as	as	SCONJ
ijassa-1442	370	15	privacy	privacy	NOUN
ijassa-1442	370	16	integration	integration	NOUN
ijassa-1442	370	17	reduces	reduce	VERB
ijassa-1442	370	18	stability	stability	NOUN
ijassa-1442	370	19	in	in	ADP
ijassa-1442	370	20	an	an	DET
ijassa-1442	370	21	already	already	ADV
ijassa-1442	370	22	unstable	unstable	ADJ
ijassa-1442	370	23	model	model	NOUN
ijassa-1442	370	24	.	.	PUNCT
ijassa-1442	371	1	increasing	increase	VERB
ijassa-1442	371	2	fairness	fairness	NOUN
ijassa-1442	371	3	may	may	AUX
ijassa-1442	371	4	require	require	VERB
ijassa-1442	371	5	strengthening	strengthen	VERB
ijassa-1442	371	6	the	the	DET
ijassa-1442	371	7	adversary	adversary	NOUN
ijassa-1442	371	8	,	,	PUNCT
ijassa-1442	371	9	which	which	PRON
ijassa-1442	371	10	further	far	ADV
ijassa-1442	371	11	adds	add	VERB
ijassa-1442	371	12	to	to	ADP
ijassa-1442	371	13	the	the	DET
ijassa-1442	371	14	instability	instability	NOUN
ijassa-1442	371	15	.	.	PUNCT
ijassa-1442	372	1	references	reference	NOUN
ijassa-1442	372	2	1	1	NUM
ijassa-1442	372	3	.	.	PUNCT
ijassa-1442	373	1	abadi	abadi	PROPN
ijassa-1442	373	2	,	,	PUNCT
ijassa-1442	373	3	m.	m.	NOUN
ijassa-1442	373	4	,	,	PUNCT
ijassa-1442	373	5	chu	chu	PROPN
ijassa-1442	373	6	,	,	PUNCT
ijassa-1442	373	7	a.	a.	NOUN
ijassa-1442	373	8	,	,	PUNCT
ijassa-1442	373	9	goodfellow	goodfellow	PROPN
ijassa-1442	373	10	,	,	PUNCT
ijassa-1442	373	11	i.	i.	PROPN
ijassa-1442	373	12	,	,	PUNCT
ijassa-1442	373	13	mcmahan	mcmahan	PROPN
ijassa-1442	373	14	,	,	PUNCT
ijassa-1442	373	15	h.	h.	PROPN
ijassa-1442	373	16	b.	b.	PROPN
ijassa-1442	373	17	,	,	PUNCT
ijassa-1442	373	18	mironov	mironov	PROPN
ijassa-1442	373	19	,	,	PUNCT
ijassa-1442	373	20	i.	i.	NOUN
ijassa-1442	373	21	,	,	PUNCT
ijassa-1442	373	22	et	et	PROPN
ijassa-1442	373	23	al	al	PROPN
ijassa-1442	373	24	.	.	PUNCT
ijassa-1442	373	25	(	(	PUNCT
ijassa-1442	373	26	2016	2016	NUM
ijassa-1442	373	27	)	)	PUNCT
ijassa-1442	373	28	.	.	PUNCT
ijassa-1442	374	1	deep	deep	ADJ
ijassa-1442	374	2	learning	learn	VERB
ijassa-1442	374	3	with	with	ADP
ijassa-1442	374	4	differential	differential	ADJ
ijassa-1442	374	5	privacy	privacy	NOUN
ijassa-1442	374	6	,	,	PUNCT
ijassa-1442	374	7	proceedings	proceeding	NOUN
ijassa-1442	374	8	of	of	ADP
ijassa-1442	374	9	the	the	DET
ijassa-1442	374	10	2016	2016	NUM
ijassa-1442	374	11	acm	acm	PROPN
ijassa-1442	374	12	sigsac	sigsac	NOUN
ijassa-1442	374	13	conference	conference	NOUN
ijassa-1442	374	14	on	on	ADP
ijassa-1442	374	15	computer	computer	NOUN
ijassa-1442	374	16	and	and	CCONJ
ijassa-1442	374	17	communications	communication	NOUN
ijassa-1442	374	18	security	security	NOUN
ijassa-1442	374	19	–	–	PUNCT
ijassa-1442	374	20	ccs'16	ccs'16	PROPN
ijassa-1442	374	21	.	.	PUNCT
ijassa-1442	375	1	vienna	vienna	PROPN
ijassa-1442	375	2	,	,	PUNCT
ijassa-1442	375	3	austria	austria	PROPN
ijassa-1442	375	4	,	,	PUNCT
ijassa-1442	375	5	308–318	308–318	NUM
ijassa-1442	375	6	,	,	PUNCT
ijassa-1442	375	7	https://doi.org/10.1145/2976749.2978318	https://doi.org/10.1145/2976749.2978318	X
ijassa-1442	375	8	2	2	NUM
ijassa-1442	375	9	.	.	NOUN
ijassa-1442	375	10	bagdasaryan	bagdasaryan	ADJ
ijassa-1442	375	11	,	,	PUNCT
ijassa-1442	375	12	e.	e.	PROPN
ijassa-1442	375	13	,	,	PUNCT
ijassa-1442	375	14	&	&	CCONJ
ijassa-1442	375	15	shmatikov	shmatikov	PROPN
ijassa-1442	375	16	,	,	PUNCT
ijassa-1442	375	17	v.	v.	PROPN
ijassa-1442	375	18	(	(	PUNCT
ijassa-1442	375	19	2019	2019	NUM
ijassa-1442	375	20	)	)	PUNCT
ijassa-1442	375	21	.	.	PUNCT
ijassa-1442	376	1	differential	differential	PROPN
ijassa-1442	376	2	privacy	privacy	NOUN
ijassa-1442	376	3	has	have	VERB
ijassa-1442	376	4	disparate	disparate	ADJ
ijassa-1442	376	5	impact	impact	NOUN
ijassa-1442	376	6	on	on	ADP
ijassa-1442	376	7	model	model	NOUN
ijassa-1442	376	8	accuracy	accuracy	NOUN
ijassa-1442	376	9	.	.	PUNCT
ijassa-1442	377	1	arxiv:1905.12101	arxiv:1905.12101	NOUN
ijassa-1442	377	2	,	,	PUNCT
ijassa-1442	377	3	[	[	X
ijassa-1442	377	4	online	online	X
ijassa-1442	377	5	]	]	X
ijassa-1442	377	6	.	.	PUNCT
ijassa-1442	378	1	available	available	ADJ
ijassa-1442	378	2	:	:	PUNCT
ijassa-1442	379	1	https://arxiv.org/abs/1905.12101	https://arxiv.org/abs/1905.12101	NOUN
ijassa-1442	379	2	3	3	X
ijassa-1442	379	3	.	.	X
ijassa-1442	379	4	baig	baig	PROPN
ijassa-1442	379	5	,	,	PUNCT
ijassa-1442	379	6	s.	s.	PROPN
ijassa-1442	379	7	m.	m.	PROPN
ijassa-1442	379	8	(	(	PUNCT
ijassa-1442	379	9	2022	2022	NUM
ijassa-1442	379	10	,	,	PUNCT
ijassa-1442	379	11	february	february	PROPN
ijassa-1442	379	12	2	2	NUM
ijassa-1442	379	13	)	)	PUNCT
ijassa-1442	379	14	stochastic	stochastic	ADJ
ijassa-1442	379	15	gradient	gradient	ADJ
ijassa-1442	379	16	descent	descent	NOUN
ijassa-1442	379	17	algorithm	algorithm	NOUN
ijassa-1442	379	18	(	(	PUNCT
ijassa-1442	379	19	sgd	sgd	PROPN
ijassa-1442	379	20	)	)	PUNCT
ijassa-1442	379	21	.	.	PUNCT
ijassa-1442	380	1	[	[	X
ijassa-1442	380	2	online	online	X
ijassa-1442	380	3	]	]	X
ijassa-1442	380	4	.	.	PUNCT
ijassa-1442	381	1	available	available	ADJ
ijassa-1442	381	2	:	:	PUNCT
ijassa-1442	382	1	https://www.researchgate.net/publication/358769475_stochastic	https://www.researchgate.net/publication/358769475_stochastic	ADJ
ijassa-1442	382	2	_	_	PRON
ijassa-1442	382	3	gradient_descent_algorithm_sgd	gradient_descent_algorithm_sgd	X
ijassa-1442	383	1	4	4	X
ijassa-1442	383	2	.	.	X
ijassa-1442	383	3	calmon	calmon	ADJ
ijassa-1442	383	4	,	,	PUNCT
ijassa-1442	383	5	f.	f.	PROPN
ijassa-1442	383	6	,	,	PUNCT
ijassa-1442	383	7	wei	wei	PROPN
ijassa-1442	383	8	,	,	PUNCT
ijassa-1442	383	9	d.	d.	PROPN
ijassa-1442	383	10	,	,	PUNCT
ijassa-1442	383	11	vinzamuri	vinzamuri	PROPN
ijassa-1442	383	12	,	,	PUNCT
ijassa-1442	383	13	b.	b.	PROPN
ijassa-1442	383	14	,	,	PUNCT
ijassa-1442	383	15	ramamurthy	ramamurthy	ADJ
ijassa-1442	383	16	,	,	PUNCT
ijassa-1442	383	17	k.	k.	PROPN
ijassa-1442	383	18	n.	n.	PROPN
ijassa-1442	383	19	,	,	PUNCT
ijassa-1442	383	20	&	&	CCONJ
ijassa-1442	383	21	varshney	varshney	NOUN
ijassa-1442	383	22	,	,	PUNCT
ijassa-1442	383	23	k.	k.	PROPN
ijassa-1442	383	24	r.	r.	PROPN
ijassa-1442	383	25	(	(	PUNCT
ijassa-1442	383	26	2017	2017	NUM
ijassa-1442	383	27	)	)	PUNCT
ijassa-1442	383	28	.	.	PUNCT
ijassa-1442	384	1	optimized	optimize	VERB
ijassa-1442	384	2	pre	pre	ADJ
ijassa-1442	384	3	-	-	ADJ
ijassa-1442	384	4	processing	processing	NOUN
ijassa-1442	384	5	for	for	ADP
ijassa-1442	384	6	discrimination	discrimination	NOUN
ijassa-1442	384	7	prevention	prevention	NOUN
ijassa-1442	384	8	,	,	PUNCT
ijassa-1442	384	9	proc	proc	NOUN
ijassa-1442	384	10	.	.	PROPN
ijassa-1442	385	1	of	of	ADP
ijassa-1442	385	2	neural	neural	ADJ
ijassa-1442	385	3	information	information	NOUN
ijassa-1442	385	4	processing	processing	NOUN
ijassa-1442	385	5	systems	system	NOUN
ijassa-1442	385	6	31	31	NUM
ijassa-1442	385	7	(	(	PUNCT
ijassa-1442	385	8	nips	nip	NOUN
ijassa-1442	385	9	2017	2017	NUM
ijassa-1442	385	10	)	)	PUNCT
ijassa-1442	385	11	.	.	PUNCT
ijassa-1442	386	1	long	long	ADJ
ijassa-1442	386	2	beach	beach	NOUN
ijassa-1442	386	3	,	,	PUNCT
ijassa-1442	386	4	ca	ca	NOUN
ijassa-1442	386	5	,	,	PUNCT
ijassa-1442	386	6	https://doi.org/10.48550/	https://doi.org/10.48550/	PROPN
ijassa-1442	386	7	arxiv.1704.03354	arxiv.1704.03354	PRON
ijassa-1442	386	8	5	5	NUM
ijassa-1442	386	9	.	.	PUNCT
ijassa-1442	387	1	chawla	chawla	PROPN
ijassa-1442	387	2	,	,	PUNCT
ijassa-1442	387	3	n.	n.	PROPN
ijassa-1442	387	4	v.	v.	PROPN
ijassa-1442	387	5	,	,	PUNCT
ijassa-1442	387	6	bowyer	bowyer	PROPN
ijassa-1442	387	7	,	,	PUNCT
ijassa-1442	387	8	k.	k.	PROPN
ijassa-1442	387	9	w.	w.	PROPN
ijassa-1442	387	10	,	,	PUNCT
ijassa-1442	387	11	hall	hall	PROPN
ijassa-1442	387	12	,	,	PUNCT
ijassa-1442	387	13	l.	l.	PROPN
ijassa-1442	387	14	o.	o.	PROPN
ijassa-1442	387	15	,	,	PUNCT
ijassa-1442	387	16	&	&	CCONJ
ijassa-1442	387	17	kegelmeyer	kegelmeyer	PROPN
ijassa-1442	387	18	,	,	PUNCT
ijassa-1442	387	19	w.	w.	PROPN
ijassa-1442	387	20	p.	p.	PROPN
ijassa-1442	387	21	(	(	PUNCT
ijassa-1442	387	22	2002	2002	NUM
ijassa-1442	387	23	)	)	PUNCT
ijassa-1442	387	24	.	.	PUNCT
ijassa-1442	388	1	smote	smote	VERB
ijassa-1442	388	2	:	:	PUNCT
ijassa-1442	388	3	synthetic	synthetic	ADJ
ijassa-1442	388	4	minority	minority	NOUN
ijassa-1442	388	5	over	over	ADP
ijassa-1442	388	6	-	-	PUNCT
ijassa-1442	388	7	sampling	sample	VERB
ijassa-1442	388	8	technique	technique	NOUN
ijassa-1442	388	9	,	,	PUNCT
ijassa-1442	388	10	journal	journal	NOUN
ijassa-1442	388	11	of	of	ADP
ijassa-1442	388	12	artificial	artificial	ADJ
ijassa-1442	388	13	intelligence	intelligence	NOUN
ijassa-1442	388	14	research	research	NOUN
ijassa-1442	388	15	,	,	PUNCT
ijassa-1442	388	16	16	16	NUM
ijassa-1442	388	17	,	,	PUNCT
ijassa-1442	388	18	321–357	321–357	NUM
ijassa-1442	388	19	,	,	PUNCT
ijassa-1442	388	20	https://doi.org/10.1613/jair.953	https://doi.org/10.1613/jair.953	NOUN
ijassa-1442	388	21	6	6	NUM
ijassa-1442	388	22	.	.	PUNCT
ijassa-1442	389	1	creager	creager	PROPN
ijassa-1442	389	2	,	,	PUNCT
ijassa-1442	389	3	e.	e.	PROPN
ijassa-1442	389	4	,	,	PUNCT
ijassa-1442	389	5	madras	madras	PROPN
ijassa-1442	389	6	,	,	PUNCT
ijassa-1442	389	7	d.	d.	PROPN
ijassa-1442	389	8	,	,	PUNCT
ijassa-1442	389	9	jacobsen	jacobsen	PROPN
ijassa-1442	389	10	,	,	PUNCT
ijassa-1442	389	11	j.-h	j.-h	PROPN
ijassa-1442	389	12	.	.	PUNCT
ijassa-1442	389	13	,	,	PUNCT
ijassa-1442	389	14	weis	weis	PROPN
ijassa-1442	389	15	,	,	PUNCT
ijassa-1442	389	16	m.	m.	NOUN
ijassa-1442	389	17	a.	a.	PROPN
ijassa-1442	389	18	,	,	PUNCT
ijassa-1442	389	19	swersky	swersky	NOUN
ijassa-1442	389	20	,	,	PUNCT
ijassa-1442	389	21	k.	k.	PROPN
ijassa-1442	389	22	,	,	PUNCT
ijassa-1442	389	23	et	et	PROPN
ijassa-1442	389	24	al	al	PROPN
ijassa-1442	389	25	.	.	PROPN
ijassa-1442	389	26	(	(	PUNCT
ijassa-1442	389	27	2019	2019	NUM
ijassa-1442	389	28	)	)	PUNCT
ijassa-1442	389	29	.	.	PUNCT
ijassa-1442	390	1	flexibly	flexibly	ADV
ijassa-1442	390	2	fair	fair	ADJ
ijassa-1442	390	3	representation	representation	NOUN
ijassa-1442	390	4	learning	learning	NOUN
ijassa-1442	390	5	by	by	ADP
ijassa-1442	390	6	disentanglement	disentanglement	NOUN
ijassa-1442	390	7	.	.	PUNCT
ijassa-1442	390	8	arxiv:1906.02589	arxiv:1906.02589	PROPN
ijassa-1442	390	9	,	,	PUNCT
ijassa-1442	391	1	[	[	X
ijassa-1442	391	2	online	online	X
ijassa-1442	391	3	]	]	X
ijassa-1442	391	4	.	.	PUNCT
ijassa-1442	392	1	available	available	ADJ
ijassa-1442	392	2	:	:	PUNCT
ijassa-1442	392	3	https://arxiv.org/abs/1906.02589	https://arxiv.org/abs/1906.02589	NOUN
ijassa-1442	392	4	58	58	NUM
ijassa-1442	392	5	a.	a.	NOUN
ijassa-1442	392	6	eponeshnikov	eponeshnikov	PROPN
ijassa-1442	392	7	,	,	PUNCT
ijassa-1442	392	8	r.	r.	PROPN
ijassa-1442	392	9	sabitov	sabitov	PROPN
ijassa-1442	392	10	,	,	PUNCT
ijassa-1442	392	11	g.	g.	PROPN
ijassa-1442	392	12	smirnova	smirnova	PROPN
ijassa-1442	392	13	,	,	PUNCT
ijassa-1442	392	14	sh	sh	PROPN
ijassa-1442	392	15	.	.	PUNCT
ijassa-1442	392	16	sabitov	sabitov	PROPN
ijassa-1442	392	17	copyright	copyright	NOUN
ijassa-1442	393	1	©	©	PROPN
ijassa-1442	393	2	2023	2023	NUM
ijassa-1442	393	3	assa	assa	PROPN
ijassa-1442	393	4	adv	adv	PROPN
ijassa-1442	393	5	.	.	PUNCT
ijassa-1442	394	1	in	in	ADP
ijassa-1442	394	2	systems	system	NOUN
ijassa-1442	394	3	science	science	NOUN
ijassa-1442	394	4	and	and	CCONJ
ijassa-1442	394	5	appl	appl	NOUN
ijassa-1442	394	6	.	.	PUNCT
ijassa-1442	395	1	(	(	PUNCT
ijassa-1442	395	2	2023	2023	NUM
ijassa-1442	395	3	)	)	PUNCT
ijassa-1442	395	4	7	7	NUM
ijassa-1442	395	5	.	.	X
ijassa-1442	395	6	sabitov	sabitov	PROPN
ijassa-1442	395	7	,	,	PUNCT
ijassa-1442	395	8	r.	r.	PROPN
ijassa-1442	395	9	a.	a.	PROPN
ijassa-1442	395	10	,	,	PUNCT
ijassa-1442	395	11	smirnova	smirnova	PROPN
ijassa-1442	395	12	,	,	PUNCT
ijassa-1442	395	13	g.	g.	PROPN
ijassa-1442	395	14	s.	s.	PROPN
ijassa-1442	395	15	,	,	PUNCT
ijassa-1442	395	16	et	et	PROPN
ijassa-1442	395	17	.	.	PUNCT
ijassa-1442	396	1	al	al	PROPN
ijassa-1442	396	2	.	.	PROPN
ijassa-1442	397	1	(	(	PUNCT
ijassa-1442	397	2	2017	2017	NUM
ijassa-1442	397	3	)	)	PUNCT
ijassa-1442	397	4	.	.	PUNCT
ijassa-1442	398	1	the	the	DET
ijassa-1442	398	2	concept	concept	NOUN
ijassa-1442	398	3	of	of	ADP
ijassa-1442	398	4	intelligent	intelligent	ADJ
ijassa-1442	398	5	tutoring	tutoring	NOUN
ijassa-1442	398	6	for	for	ADP
ijassa-1442	398	7	enterprise	enterprise	NOUN
ijassa-1442	398	8	staff	staff	NOUN
ijassa-1442	398	9	as	as	ADP
ijassa-1442	398	10	a	a	DET
ijassa-1442	398	11	component	component	NOUN
ijassa-1442	398	12	of	of	ADP
ijassa-1442	398	13	integrated	integrate	VERB
ijassa-1442	398	14	manufacturing	manufacturing	NOUN
ijassa-1442	398	15	control	control	NOUN
ijassa-1442	398	16	system	system	NOUN
ijassa-1442	398	17	development	development	NOUN
ijassa-1442	398	18	,	,	PUNCT
ijassa-1442	398	19	advances	advance	NOUN
ijassa-1442	398	20	in	in	ADP
ijassa-1442	398	21	systems	system	NOUN
ijassa-1442	398	22	science	science	NOUN
ijassa-1442	398	23	and	and	CCONJ
ijassa-1442	398	24	applications	application	NOUN
ijassa-1442	398	25	,	,	PUNCT
ijassa-1442	398	26	17(1	17(1	NUM
ijassa-1442	398	27	)	)	PUNCT
ijassa-1442	398	28	,	,	PUNCT
ijassa-1442	398	29	1–8	1–8	X
ijassa-1442	398	30	.	.	NOUN
ijassa-1442	398	31	8	8	NUM
ijassa-1442	398	32	.	.	PUNCT
ijassa-1442	399	1	dwork	dwork	PROPN
ijassa-1442	399	2	,	,	PUNCT
ijassa-1442	399	3	c.	c.	PROPN
ijassa-1442	399	4	,	,	PUNCT
ijassa-1442	399	5	hardt	hardt	PROPN
ijassa-1442	399	6	,	,	PUNCT
ijassa-1442	399	7	m.	m.	NOUN
ijassa-1442	399	8	,	,	PUNCT
ijassa-1442	399	9	pitassi	pitassi	NOUN
ijassa-1442	399	10	,	,	PUNCT
ijassa-1442	399	11	t.	t.	PROPN
ijassa-1442	399	12	,	,	PUNCT
ijassa-1442	399	13	reingold	reingold	ADJ
ijassa-1442	399	14	,	,	PUNCT
ijassa-1442	399	15	o.	o.	PROPN
ijassa-1442	399	16	,	,	PUNCT
ijassa-1442	399	17	&	&	CCONJ
ijassa-1442	399	18	zemel	zemel	PROPN
ijassa-1442	399	19	,	,	PUNCT
ijassa-1442	399	20	r.	r.	PROPN
ijassa-1442	399	21	(	(	PUNCT
ijassa-1442	399	22	2012	2012	NUM
ijassa-1442	399	23	)	)	PUNCT
ijassa-1442	399	24	.	.	PUNCT
ijassa-1442	400	1	fairness	fairness	NOUN
ijassa-1442	400	2	through	through	ADP
ijassa-1442	400	3	awareness	awareness	NOUN
ijassa-1442	400	4	,	,	PUNCT
ijassa-1442	400	5	proceedings	proceeding	NOUN
ijassa-1442	400	6	of	of	ADP
ijassa-1442	400	7	the	the	DET
ijassa-1442	400	8	3rd	3rd	ADJ
ijassa-1442	400	9	innovations	innovation	NOUN
ijassa-1442	400	10	in	in	ADP
ijassa-1442	400	11	theoretical	theoretical	ADJ
ijassa-1442	400	12	computer	computer	NOUN
ijassa-1442	400	13	science	science	NOUN
ijassa-1442	400	14	conference	conference	NOUN
ijassa-1442	400	15	(	(	PUNCT
ijassa-1442	400	16	itcs’12	itcs’12	PROPN
ijassa-1442	400	17	)	)	PUNCT
ijassa-1442	400	18	.	.	PUNCT
ijassa-1442	401	1	cambridge	cambridge	PROPN
ijassa-1442	401	2	,	,	PUNCT
ijassa-1442	401	3	usa	usa	PROPN
ijassa-1442	401	4	,	,	PUNCT
ijassa-1442	401	5	214–226	214–226	NUM
ijassa-1442	401	6	,	,	PUNCT
ijassa-1442	401	7	https://doi.org/10.1145/	https://doi.org/10.1145/	PROPN
ijassa-1442	401	8	2090236.2090255	2090236.2090255	PROPN
ijassa-1442	401	9	9	9	NUM
ijassa-1442	401	10	.	.	PUNCT
ijassa-1442	402	1	edwards	edwards	PROPN
ijassa-1442	402	2	,	,	PUNCT
ijassa-1442	402	3	h.	h.	PROPN
ijassa-1442	402	4	,	,	PUNCT
ijassa-1442	402	5	&	&	CCONJ
ijassa-1442	402	6	storkey	storkey	PROPN
ijassa-1442	402	7	,	,	PUNCT
ijassa-1442	402	8	a.	a.	NOUN
ijassa-1442	402	9	(	(	PUNCT
ijassa-1442	402	10	2016	2016	NUM
ijassa-1442	402	11	)	)	PUNCT
ijassa-1442	402	12	.	.	PUNCT
ijassa-1442	403	1	censoring	censor	VERB
ijassa-1442	403	2	representations	representation	NOUN
ijassa-1442	403	3	with	with	ADP
ijassa-1442	403	4	an	an	DET
ijassa-1442	403	5	adversary	adversary	NOUN
ijassa-1442	403	6	.	.	PUNCT
ijassa-1442	404	1	arxiv:1511.05897	arxiv:1511.05897	PROPN
ijassa-1442	404	2	,	,	PUNCT
ijassa-1442	405	1	[	[	X
ijassa-1442	405	2	online	online	X
ijassa-1442	405	3	]	]	X
ijassa-1442	405	4	.	.	PUNCT
ijassa-1442	406	1	available	available	ADJ
ijassa-1442	406	2	:	:	PUNCT
ijassa-1442	406	3	https://arxiv.org/abs/1511.05897	https://arxiv.org/abs/1511.05897	PROPN
ijassa-1442	406	4	10	10	NUM
ijassa-1442	406	5	.	.	PUNCT
ijassa-1442	407	1	elazar	elazar	NOUN
ijassa-1442	407	2	,	,	PUNCT
ijassa-1442	407	3	y.	y.	PROPN
ijassa-1442	407	4	,	,	PUNCT
ijassa-1442	407	5	&	&	CCONJ
ijassa-1442	407	6	goldberg	goldberg	PROPN
ijassa-1442	407	7	,	,	PUNCT
ijassa-1442	407	8	y.	y.	PROPN
ijassa-1442	407	9	(	(	PUNCT
ijassa-1442	407	10	2018	2018	NUM
ijassa-1442	407	11	)	)	PUNCT
ijassa-1442	407	12	.	.	PUNCT
ijassa-1442	408	1	adversarial	adversarial	ADJ
ijassa-1442	408	2	removal	removal	NOUN
ijassa-1442	408	3	of	of	ADP
ijassa-1442	408	4	demographic	demographic	ADJ
ijassa-1442	408	5	attributes	attribute	NOUN
ijassa-1442	408	6	from	from	ADP
ijassa-1442	408	7	text	text	NOUN
ijassa-1442	408	8	data	datum	NOUN
ijassa-1442	408	9	.	.	PUNCT
ijassa-1442	409	1	arxiv:1808.06640	arxiv:1808.06640	PROPN
ijassa-1442	409	2	,	,	PUNCT
ijassa-1442	409	3	[	[	X
ijassa-1442	409	4	online	online	X
ijassa-1442	409	5	]	]	X
ijassa-1442	409	6	.	.	PUNCT
ijassa-1442	410	1	available	available	ADJ
ijassa-1442	410	2	:	:	PUNCT
ijassa-1442	410	3	https://arxiv.org/abs/1808.06640	https://arxiv.org/abs/1808.06640	ADJ
ijassa-1442	410	4	11	11	NUM
ijassa-1442	410	5	.	.	PUNCT
ijassa-1442	410	6	farrand	farrand	NOUN
ijassa-1442	410	7	,	,	PUNCT
ijassa-1442	410	8	t.	t.	PROPN
ijassa-1442	410	9	,	,	PUNCT
ijassa-1442	410	10	mireshghallah	mireshghallah	PROPN
ijassa-1442	410	11	,	,	PUNCT
ijassa-1442	410	12	f.	f.	PROPN
ijassa-1442	410	13	,	,	PUNCT
ijassa-1442	410	14	singh	singh	PROPN
ijassa-1442	410	15	,	,	PUNCT
ijassa-1442	410	16	s.	s.	PROPN
ijassa-1442	410	17	&	&	CCONJ
ijassa-1442	410	18	trask	trask	PROPN
ijassa-1442	410	19	,	,	PUNCT
ijassa-1442	410	20	a.	a.	PROPN
ijassa-1442	410	21	(	(	PUNCT
ijassa-1442	410	22	2020	2020	NUM
ijassa-1442	410	23	)	)	PUNCT
ijassa-1442	410	24	.	.	PUNCT
ijassa-1442	411	1	neither	neither	CCONJ
ijassa-1442	411	2	private	private	ADJ
ijassa-1442	411	3	nor	nor	CCONJ
ijassa-1442	411	4	fair	fair	ADJ
ijassa-1442	411	5	:	:	PUNCT
ijassa-1442	411	6	impact	impact	NOUN
ijassa-1442	411	7	of	of	ADP
ijassa-1442	411	8	data	datum	NOUN
ijassa-1442	411	9	imbalance	imbalance	NOUN
ijassa-1442	411	10	on	on	ADP
ijassa-1442	411	11	utility	utility	NOUN
ijassa-1442	411	12	and	and	CCONJ
ijassa-1442	411	13	fairness	fairness	NOUN
ijassa-1442	411	14	in	in	ADP
ijassa-1442	411	15	differential	differential	ADJ
ijassa-1442	411	16	privacy	privacy	NOUN
ijassa-1442	411	17	.	.	PUNCT
ijassa-1442	412	1	arxiv:2009.06389	arxiv:2009.06389	PROPN
ijassa-1442	412	2	,	,	PUNCT
ijassa-1442	413	1	[	[	X
ijassa-1442	413	2	online	online	X
ijassa-1442	413	3	]	]	X
ijassa-1442	413	4	.	.	PUNCT
ijassa-1442	414	1	available	available	ADJ
ijassa-1442	414	2	:	:	PUNCT
ijassa-1442	414	3	https://arxiv.org/abs/2009.06389	https://arxiv.org/abs/2009.06389	NOUN
ijassa-1442	414	4	12	12	NUM
ijassa-1442	414	5	.	.	PUNCT
ijassa-1442	415	1	hardt	hardt	PROPN
ijassa-1442	415	2	,	,	PUNCT
ijassa-1442	415	3	m.	m.	NOUN
ijassa-1442	415	4	,	,	PUNCT
ijassa-1442	415	5	price	price	NOUN
ijassa-1442	415	6	,	,	PUNCT
ijassa-1442	415	7	e.	e.	PROPN
ijassa-1442	415	8	,	,	PUNCT
ijassa-1442	415	9	&	&	CCONJ
ijassa-1442	415	10	srebro	srebro	PROPN
ijassa-1442	415	11	,	,	PUNCT
ijassa-1442	415	12	n.	n.	PROPN
ijassa-1442	415	13	(	(	PUNCT
ijassa-1442	415	14	2016	2016	NUM
ijassa-1442	415	15	)	)	PUNCT
ijassa-1442	415	16	.	.	PUNCT
ijassa-1442	416	1	equality	equality	NOUN
ijassa-1442	416	2	of	of	ADP
ijassa-1442	416	3	opportunity	opportunity	NOUN
ijassa-1442	416	4	in	in	ADP
ijassa-1442	416	5	supervised	supervised	ADJ
ijassa-1442	416	6	learning	learning	NOUN
ijassa-1442	416	7	.	.	PUNCT
ijassa-1442	417	1	arxiv:1610.02413	arxiv:1610.02413	PROPN
ijassa-1442	417	2	,	,	PUNCT
ijassa-1442	418	1	[	[	X
ijassa-1442	418	2	online	online	X
ijassa-1442	418	3	]	]	X
ijassa-1442	418	4	.	.	PUNCT
ijassa-1442	419	1	available	available	ADJ
ijassa-1442	419	2	:	:	PUNCT
ijassa-1442	419	3	https://arxiv.org/abs/1610.02413	https://arxiv.org/abs/1610.02413	PROPN
ijassa-1442	419	4	13	13	NUM
ijassa-1442	419	5	.	.	PUNCT
ijassa-1442	420	1	huang	huang	PROPN
ijassa-1442	420	2	,	,	PUNCT
ijassa-1442	420	3	g.	g.	PROPN
ijassa-1442	420	4	,	,	PUNCT
ijassa-1442	420	5	liu	liu	PROPN
ijassa-1442	420	6	,	,	PUNCT
ijassa-1442	420	7	z.	z.	PROPN
ijassa-1442	420	8	,	,	PUNCT
ijassa-1442	420	9	van	van	PROPN
ijassa-1442	420	10	der	der	NOUN
ijassa-1442	420	11	maaten	maaten	VERB
ijassa-1442	420	12	,	,	PUNCT
ijassa-1442	420	13	l.	l.	PROPN
ijassa-1442	420	14	,	,	PUNCT
ijassa-1442	420	15	&	&	CCONJ
ijassa-1442	420	16	weinberger	weinberger	PROPN
ijassa-1442	420	17	,	,	PUNCT
ijassa-1442	420	18	k.	k.	PROPN
ijassa-1442	420	19	(	(	PUNCT
ijassa-1442	420	20	2018	2018	NUM
ijassa-1442	420	21	)	)	PUNCT
ijassa-1442	420	22	.	.	PUNCT
ijassa-1442	421	1	densely	densely	ADV
ijassa-1442	421	2	connected	connect	VERB
ijassa-1442	421	3	convolutional	convolutional	ADJ
ijassa-1442	421	4	networks	network	NOUN
ijassa-1442	421	5	.	.	PUNCT
ijassa-1442	422	1	arxiv	arxiv	NOUN
ijassa-1442	422	2	:	:	PUNCT
ijassa-1442	422	3	1608.06993	1608.06993	NUM
ijassa-1442	422	4	,	,	PUNCT
ijassa-1442	423	1	[	[	X
ijassa-1442	423	2	online	online	X
ijassa-1442	423	3	]	]	X
ijassa-1442	423	4	.	.	PUNCT
ijassa-1442	424	1	available	available	ADJ
ijassa-1442	424	2	:	:	PUNCT
ijassa-1442	424	3	https://arxiv.org/abs/1608.06993	https://arxiv.org/abs/1608.06993	NOUN
ijassa-1442	424	4	14	14	NUM
ijassa-1442	424	5	.	.	PUNCT
ijassa-1442	425	1	jagielski	jagielski	PROPN
ijassa-1442	425	2	,	,	PUNCT
ijassa-1442	425	3	m.	m.	NOUN
ijassa-1442	425	4	,	,	PUNCT
ijassa-1442	425	5	kearns	kearn	NOUN
ijassa-1442	425	6	,	,	PUNCT
ijassa-1442	425	7	m.	m.	NOUN
ijassa-1442	425	8	,	,	PUNCT
ijassa-1442	425	9	mao	mao	PROPN
ijassa-1442	425	10	,	,	PUNCT
ijassa-1442	425	11	j.	j.	PROPN
ijassa-1442	425	12	,	,	PUNCT
ijassa-1442	425	13	oprea	oprea	PROPN
ijassa-1442	425	14	,	,	PUNCT
ijassa-1442	425	15	a.	a.	PROPN
ijassa-1442	425	16	,	,	PUNCT
ijassa-1442	425	17	roth	roth	PROPN
ijassa-1442	425	18	,	,	PUNCT
ijassa-1442	425	19	a.	a.	NOUN
ijassa-1442	425	20	,	,	PUNCT
ijassa-1442	425	21	et	et	PROPN
ijassa-1442	425	22	.	.	PUNCT
ijassa-1442	426	1	al	al	PROPN
ijassa-1442	426	2	.	.	PROPN
ijassa-1442	427	1	(	(	PUNCT
ijassa-1442	427	2	2019	2019	NUM
ijassa-1442	427	3	)	)	PUNCT
ijassa-1442	427	4	.	.	PUNCT
ijassa-1442	428	1	differentially	differentially	ADV
ijassa-1442	428	2	private	private	ADJ
ijassa-1442	428	3	fair	fair	ADJ
ijassa-1442	428	4	learning	learning	NOUN
ijassa-1442	428	5	.	.	PUNCT
ijassa-1442	429	1	arxiv:1812.02696	arxiv:1812.02696	NOUN
ijassa-1442	429	2	,	,	PUNCT
ijassa-1442	430	1	[	[	X
ijassa-1442	430	2	online	online	X
ijassa-1442	430	3	]	]	X
ijassa-1442	430	4	.	.	PUNCT
ijassa-1442	431	1	available	available	ADJ
ijassa-1442	431	2	:	:	PUNCT
ijassa-1442	431	3	https://arxiv.org/abs/1812.02696	https://arxiv.org/abs/1812.02696	NOUN
ijassa-1442	431	4	15	15	NUM
ijassa-1442	431	5	.	.	PUNCT
ijassa-1442	432	1	kamiran	kamiran	PROPN
ijassa-1442	432	2	,	,	PUNCT
ijassa-1442	432	3	f.	f.	PROPN
ijassa-1442	432	4	,	,	PUNCT
ijassa-1442	432	5	&	&	CCONJ
ijassa-1442	432	6	calders	calder	NOUN
ijassa-1442	432	7	,	,	PUNCT
ijassa-1442	432	8	t.	t.	PROPN
ijassa-1442	432	9	(	(	PUNCT
ijassa-1442	432	10	2011	2011	NUM
ijassa-1442	432	11	)	)	PUNCT
ijassa-1442	432	12	.	.	PUNCT
ijassa-1442	433	1	data	datum	NOUN
ijassa-1442	433	2	preprocessing	preprocesse	VERB
ijassa-1442	433	3	techniques	technique	NOUN
ijassa-1442	433	4	for	for	ADP
ijassa-1442	433	5	classification	classification	NOUN
ijassa-1442	433	6	without	without	ADP
ijassa-1442	433	7	discrimination	discrimination	NOUN
ijassa-1442	433	8	,	,	PUNCT
ijassa-1442	433	9	knowledge	knowledge	NOUN
ijassa-1442	433	10	and	and	CCONJ
ijassa-1442	433	11	information	information	NOUN
ijassa-1442	433	12	systems	system	NOUN
ijassa-1442	433	13	,	,	PUNCT
ijassa-1442	433	14	33	33	NUM
ijassa-1442	433	15	,	,	PUNCT
ijassa-1442	433	16	1–33	1–33	NUM
ijassa-1442	433	17	,	,	PUNCT
ijassa-1442	433	18	https://doi.org/10.1007/s10115-011-0463-8	https://doi.org/10.1007/s10115-011-0463-8	NOUN
ijassa-1442	433	19	16	16	NUM
ijassa-1442	433	20	.	.	PUNCT
ijassa-1442	434	1	lyu	lyu	NOUN
ijassa-1442	434	2	,	,	PUNCT
ijassa-1442	434	3	l.	l.	PROPN
ijassa-1442	434	4	,	,	PUNCT
ijassa-1442	434	5	he	he	PRON
ijassa-1442	434	6	,	,	PUNCT
ijassa-1442	434	7	x.	x.	PROPN
ijassa-1442	434	8	,	,	PUNCT
ijassa-1442	434	9	&	&	CCONJ
ijassa-1442	434	10	li	li	PROPN
ijassa-1442	434	11	,	,	PUNCT
ijassa-1442	434	12	y.	y.	PROPN
ijassa-1442	434	13	(	(	PUNCT
ijassa-1442	434	14	2020	2020	NUM
ijassa-1442	434	15	)	)	PUNCT
ijassa-1442	434	16	.	.	PUNCT
ijassa-1442	435	1	differentially	differentially	ADV
ijassa-1442	435	2	private	private	ADJ
ijassa-1442	435	3	representation	representation	NOUN
ijassa-1442	435	4	for	for	ADP
ijassa-1442	435	5	nlp	nlp	NOUN
ijassa-1442	435	6	:	:	PUNCT
ijassa-1442	435	7	formal	formal	ADJ
ijassa-1442	435	8	guarantee	guarantee	NOUN
ijassa-1442	435	9	and	and	CCONJ
ijassa-1442	435	10	an	an	DET
ijassa-1442	435	11	empirical	empirical	ADJ
ijassa-1442	435	12	study	study	NOUN
ijassa-1442	435	13	on	on	ADP
ijassa-1442	435	14	privacy	privacy	NOUN
ijassa-1442	435	15	and	and	CCONJ
ijassa-1442	435	16	fairness	fairness	NOUN
ijassa-1442	435	17	.	.	PUNCT
ijassa-1442	436	1	arxiv:2010.01285	arxiv:2010.01285	PROPN
ijassa-1442	436	2	,	,	PUNCT
ijassa-1442	437	1	[	[	X
ijassa-1442	437	2	online	online	X
ijassa-1442	437	3	]	]	X
ijassa-1442	437	4	.	.	PUNCT
ijassa-1442	438	1	available	available	ADJ
ijassa-1442	438	2	:	:	PUNCT
ijassa-1442	438	3	https://arxiv.org/abs/2010.01285	https://arxiv.org/abs/2010.01285	PROPN
ijassa-1442	439	1	17	17	NUM
ijassa-1442	439	2	.	.	PUNCT
ijassa-1442	439	3	madras	madras	PROPN
ijassa-1442	439	4	,	,	PUNCT
ijassa-1442	439	5	d.	d.	PROPN
ijassa-1442	439	6	,	,	PUNCT
ijassa-1442	439	7	creager	creager	PROPN
ijassa-1442	439	8	,	,	PUNCT
ijassa-1442	439	9	e.	e.	PROPN
ijassa-1442	439	10	,	,	PUNCT
ijassa-1442	439	11	pitassi	pitassi	PROPN
ijassa-1442	439	12	,	,	PUNCT
ijassa-1442	439	13	t.	t.	PROPN
ijassa-1442	439	14	,	,	PUNCT
ijassa-1442	439	15	&	&	CCONJ
ijassa-1442	439	16	zemel	zemel	PROPN
ijassa-1442	439	17	,	,	PUNCT
ijassa-1442	439	18	r.	r.	PROPN
ijassa-1442	439	19	(	(	PUNCT
ijassa-1442	439	20	2018	2018	NUM
ijassa-1442	439	21	)	)	PUNCT
ijassa-1442	439	22	.	.	PUNCT
ijassa-1442	440	1	learning	learn	VERB
ijassa-1442	440	2	adversarially	adversarially	ADV
ijassa-1442	440	3	fair	fair	ADJ
ijassa-1442	440	4	and	and	CCONJ
ijassa-1442	440	5	transferable	transferable	ADJ
ijassa-1442	440	6	representations	representation	NOUN
ijassa-1442	440	7	.	.	PUNCT
ijassa-1442	441	1	arxiv:1802.06309	arxiv:1802.06309	NOUN
ijassa-1442	441	2	,	,	PUNCT
ijassa-1442	442	1	[	[	X
ijassa-1442	442	2	online	online	X
ijassa-1442	442	3	]	]	X
ijassa-1442	442	4	.	.	PUNCT
ijassa-1442	443	1	available	available	ADJ
ijassa-1442	443	2	:	:	PUNCT
ijassa-1442	443	3	https://arxiv.org/abs/1802.06309	https://arxiv.org/abs/1802.06309	NOUN
ijassa-1442	443	4	18	18	NUM
ijassa-1442	443	5	.	.	PUNCT
ijassa-1442	444	1	mcmahan	mcmahan	PROPN
ijassa-1442	444	2	,	,	PUNCT
ijassa-1442	444	3	h.	h.	PROPN
ijassa-1442	444	4	b.	b.	PROPN
ijassa-1442	444	5	,	,	PUNCT
ijassa-1442	444	6	ramage	ramage	NOUN
ijassa-1442	444	7	,	,	PUNCT
ijassa-1442	444	8	d.	d.	PROPN
ijassa-1442	444	9	,	,	PUNCT
ijassa-1442	444	10	talwar	talwar	PROPN
ijassa-1442	444	11	,	,	PUNCT
ijassa-1442	444	12	k.	k.	PROPN
ijassa-1442	444	13	,	,	PUNCT
ijassa-1442	444	14	&	&	CCONJ
ijassa-1442	444	15	zhang	zhang	PROPN
ijassa-1442	444	16	,	,	PUNCT
ijassa-1442	444	17	l.	l.	PROPN
ijassa-1442	444	18	(	(	PUNCT
ijassa-1442	444	19	2018	2018	NUM
ijassa-1442	444	20	)	)	PUNCT
ijassa-1442	444	21	.	.	PUNCT
ijassa-1442	445	1	learning	learn	VERB
ijassa-1442	445	2	differentially	differentially	ADV
ijassa-1442	445	3	private	private	ADJ
ijassa-1442	445	4	recurrent	recurrent	ADJ
ijassa-1442	445	5	language	language	NOUN
ijassa-1442	445	6	models	model	NOUN
ijassa-1442	445	7	.	.	PUNCT
ijassa-1442	446	1	arxiv:1710.06963	arxiv:1710.06963	VERB
ijassa-1442	446	2	,	,	PUNCT
ijassa-1442	447	1	[	[	X
ijassa-1442	447	2	online	online	X
ijassa-1442	447	3	]	]	X
ijassa-1442	447	4	.	.	PUNCT
ijassa-1442	448	1	available	available	ADJ
ijassa-1442	448	2	:	:	PUNCT
ijassa-1442	448	3	https://arxiv.org/abs/1710.06963	https://arxiv.org/abs/1710.06963	PROPN
ijassa-1442	448	4	19	19	NUM
ijassa-1442	448	5	.	.	PUNCT
ijassa-1442	448	6	mehrabi	mehrabi	NOUN
ijassa-1442	448	7	,	,	PUNCT
ijassa-1442	448	8	n.	n.	NOUN
ijassa-1442	448	9	,	,	PUNCT
ijassa-1442	448	10	morstatter	morstatter	PROPN
ijassa-1442	448	11	,	,	PUNCT
ijassa-1442	448	12	f.	f.	PROPN
ijassa-1442	448	13	,	,	PUNCT
ijassa-1442	448	14	saxena	saxena	PROPN
ijassa-1442	448	15	,	,	PUNCT
ijassa-1442	448	16	n.	n.	PROPN
ijassa-1442	448	17	,	,	PUNCT
ijassa-1442	448	18	lerman	lerman	PROPN
ijassa-1442	448	19	,	,	PUNCT
ijassa-1442	448	20	k.	k.	PROPN
ijassa-1442	448	21	&	&	CCONJ
ijassa-1442	448	22	galstyan	galstyan	PROPN
ijassa-1442	448	23	,	,	PUNCT
ijassa-1442	448	24	a.	a.	NOUN
ijassa-1442	448	25	(	(	PUNCT
ijassa-1442	448	26	2019	2019	NUM
ijassa-1442	448	27	)	)	PUNCT
ijassa-1442	448	28	.	.	PUNCT
ijassa-1442	449	1	a	a	DET
ijassa-1442	449	2	survey	survey	NOUN
ijassa-1442	449	3	on	on	ADP
ijassa-1442	449	4	bias	bias	NOUN
ijassa-1442	449	5	and	and	CCONJ
ijassa-1442	449	6	fairness	fairness	NOUN
ijassa-1442	449	7	in	in	ADP
ijassa-1442	449	8	machine	machine	NOUN
ijassa-1442	449	9	learning	learning	NOUN
ijassa-1442	449	10	.	.	PUNCT
ijassa-1442	450	1	arxiv:1908.09635	arxiv:1908.09635	PROPN
ijassa-1442	450	2	,	,	PUNCT
ijassa-1442	451	1	[	[	X
ijassa-1442	451	2	online	online	X
ijassa-1442	451	3	]	]	X
ijassa-1442	451	4	.	.	PUNCT
ijassa-1442	452	1	available	available	ADJ
ijassa-1442	452	2	:	:	PUNCT
ijassa-1442	452	3	https://arxiv.org/abs/1908.09635	https://arxiv.org/abs/1908.09635	NOUN
ijassa-1442	452	4	20	20	NUM
ijassa-1442	452	5	.	.	PUNCT
ijassa-1442	453	1	pereira	pereira	PROPN
ijassa-1442	453	2	,	,	PUNCT
ijassa-1442	453	3	m.	m.	NOUN
ijassa-1442	453	4	,	,	PUNCT
ijassa-1442	453	5	kshirsagar	kshirsagar	NOUN
ijassa-1442	453	6	,	,	PUNCT
ijassa-1442	453	7	m.	m.	NOUN
ijassa-1442	453	8	,	,	PUNCT
ijassa-1442	453	9	mukherjee	mukherjee	PROPN
ijassa-1442	453	10	,	,	PUNCT
ijassa-1442	453	11	s.	s.	PROPN
ijassa-1442	453	12	,	,	PUNCT
ijassa-1442	453	13	dodhia	dodhia	PROPN
ijassa-1442	453	14	,	,	PUNCT
ijassa-1442	453	15	r.	r.	PROPN
ijassa-1442	453	16	,	,	PUNCT
ijassa-1442	453	17	&	&	CCONJ
ijassa-1442	453	18	ferres	ferres	PROPN
ijassa-1442	453	19	,	,	PUNCT
ijassa-1442	453	20	j.	j.	PROPN
ijassa-1442	453	21	l.	l.	PROPN
ijassa-1442	453	22	(	(	PUNCT
ijassa-1442	453	23	2021	2021	NUM
ijassa-1442	453	24	)	)	PUNCT
ijassa-1442	453	25	.	.	PUNCT
ijassa-1442	454	1	an	an	DET
ijassa-1442	454	2	analysis	analysis	NOUN
ijassa-1442	454	3	of	of	ADP
ijassa-1442	454	4	the	the	DET
ijassa-1442	454	5	deployment	deployment	NOUN
ijassa-1442	454	6	of	of	ADP
ijassa-1442	454	7	models	model	NOUN
ijassa-1442	454	8	trained	train	VERB
ijassa-1442	454	9	on	on	ADP
ijassa-1442	454	10	private	private	ADJ
ijassa-1442	454	11	tabular	tabular	NOUN
ijassa-1442	454	12	synthetic	synthetic	ADJ
ijassa-1442	454	13	data	datum	NOUN
ijassa-1442	454	14	:	:	PUNCT
ijassa-1442	454	15	unexpected	unexpected	ADJ
ijassa-1442	454	16	surprises	surprise	NOUN
ijassa-1442	454	17	.	.	PUNCT
ijassa-1442	455	1	arxiv:2106.10241	arxiv:2106.10241	PROPN
ijassa-1442	455	2	,	,	PUNCT
ijassa-1442	455	3	[	[	X
ijassa-1442	455	4	online	online	X
ijassa-1442	455	5	]	]	X
ijassa-1442	455	6	.	.	PUNCT
ijassa-1442	456	1	available	available	ADJ
ijassa-1442	456	2	:	:	PUNCT
ijassa-1442	456	3	https://arxiv.org/abs/2106.10241	https://arxiv.org/abs/2106.10241	VERB
ijassa-1442	456	4	21	21	NUM
ijassa-1442	456	5	.	.	PUNCT
ijassa-1442	457	1	reddy	reddy	PROPN
ijassa-1442	457	2	,	,	PUNCT
ijassa-1442	457	3	c.	c.	PROPN
ijassa-1442	457	4	,	,	PUNCT
ijassa-1442	457	5	sharma	sharma	PROPN
ijassa-1442	457	6	,	,	PUNCT
ijassa-1442	457	7	d.	d.	PROPN
ijassa-1442	457	8	,	,	PUNCT
ijassa-1442	457	9	mehri	mehri	PROPN
ijassa-1442	457	10	,	,	PUNCT
ijassa-1442	457	11	s.	s.	PROPN
ijassa-1442	457	12	,	,	PUNCT
ijassa-1442	457	13	romero	romero	PROPN
ijassa-1442	457	14	-	-	PUNCT
ijassa-1442	457	15	soriano	soriano	PROPN
ijassa-1442	457	16	,	,	PUNCT
ijassa-1442	457	17	a.	a.	PROPN
ijassa-1442	457	18	,	,	PUNCT
ijassa-1442	457	19	shabanian	shabanian	PROPN
ijassa-1442	457	20	,	,	PUNCT
ijassa-1442	457	21	s.	s.	PROPN
ijassa-1442	457	22	,	,	PUNCT
ijassa-1442	457	23	et	et	PROPN
ijassa-1442	457	24	al	al	PROPN
ijassa-1442	457	25	.	.	PUNCT
ijassa-1442	457	26	(	(	PUNCT
ijassa-1442	457	27	2021	2021	NUM
ijassa-1442	457	28	)	)	PUNCT
ijassa-1442	457	29	.	.	PUNCT
ijassa-1442	458	1	benchmarking	benchmarke	VERB
ijassa-1442	458	2	bias	bias	NOUN
ijassa-1442	458	3	mitigation	mitigation	NOUN
ijassa-1442	458	4	algorithms	algorithm	NOUN
ijassa-1442	458	5	in	in	ADP
ijassa-1442	458	6	representation	representation	NOUN
ijassa-1442	458	7	learning	learn	VERB
ijassa-1442	458	8	through	through	ADP
ijassa-1442	458	9	fairness	fairness	NOUN
ijassa-1442	458	10	metrics	metric	NOUN
ijassa-1442	458	11	.	.	PUNCT
ijassa-1442	459	1	[	[	X
ijassa-1442	459	2	online	online	X
ijassa-1442	459	3	]	]	X
ijassa-1442	459	4	.	.	PUNCT
ijassa-1442	460	1	available	available	ADJ
ijassa-1442	460	2	:	:	PUNCT
ijassa-1442	461	1	https://openreview.net/pdf?id=otnqquewpku	https://openreview.net/pdf?id=otnqquewpku	PROPN
ijassa-1442	461	2	22	22	NUM
ijassa-1442	461	3	.	.	PUNCT
ijassa-1442	462	1	singh	singh	PROPN
ijassa-1442	462	2	,	,	PUNCT
ijassa-1442	462	3	j.	j.	PROPN
ijassa-1442	462	4	,	,	PUNCT
ijassa-1442	462	5	&	&	CCONJ
ijassa-1442	462	6	banerjee	banerjee	PROPN
ijassa-1442	462	7	,	,	PUNCT
ijassa-1442	462	8	r.	r.	PROPN
ijassa-1442	462	9	(	(	PUNCT
ijassa-1442	462	10	2019	2019	NUM
ijassa-1442	462	11	)	)	PUNCT
ijassa-1442	462	12	.	.	PUNCT
ijassa-1442	463	1	a	a	DET
ijassa-1442	463	2	study	study	NOUN
ijassa-1442	463	3	on	on	ADP
ijassa-1442	463	4	single	single	ADJ
ijassa-1442	463	5	and	and	CCONJ
ijassa-1442	463	6	multi	multi	ADJ
ijassa-1442	463	7	-	-	ADJ
ijassa-1442	463	8	layer	layer	ADJ
ijassa-1442	463	9	perceptron	perceptron	PROPN
ijassa-1442	463	10	neural	neural	ADJ
ijassa-1442	463	11	network	network	PROPN
ijassa-1442	463	12	.	.	PUNCT
ijassa-1442	464	1	proc	proc	PROPN
ijassa-1442	464	2	.	.	PUNCT
ijassa-1442	465	1	of	of	ADP
ijassa-1442	465	2	the	the	DET
ijassa-1442	465	3	2019	2019	NUM
ijassa-1442	465	4	3rd	3rd	ADJ
ijassa-1442	465	5	international	international	ADJ
ijassa-1442	465	6	conference	conference	NOUN
ijassa-1442	465	7	on	on	ADP
ijassa-1442	465	8	computing	computing	NOUN
ijassa-1442	465	9	methodologies	methodology	NOUN
ijassa-1442	465	10	and	and	CCONJ
ijassa-1442	465	11	communication	communication	NOUN
ijassa-1442	465	12	(	(	PUNCT
ijassa-1442	465	13	iccmc	iccmc	NOUN
ijassa-1442	465	14	)	)	PUNCT
ijassa-1442	465	15	.	.	PUNCT
ijassa-1442	466	1	erode	erode	PROPN
ijassa-1442	466	2	,	,	PUNCT
ijassa-1442	466	3	india	india	PROPN
ijassa-1442	466	4	,	,	PUNCT
ijassa-1442	466	5	35–40	35–40	NUM
ijassa-1442	466	6	,	,	PUNCT
ijassa-1442	466	7	https://doi.org/	https://doi.org/	VERB
ijassa-1442	466	8	10.1109	10.1109	NUM
ijassa-1442	466	9	/	/	SYM
ijassa-1442	466	10	iccmc.2019.8819775	iccmc.2019.8819775	PROPN
ijassa-1442	466	11	.	.	PUNCT
ijassa-1442	467	1	23	23	NUM
ijassa-1442	467	2	.	.	X
ijassa-1442	468	1	tato	tato	PROPN
ijassa-1442	468	2	,	,	PUNCT
ijassa-1442	468	3	a.	a.	PROPN
ijassa-1442	468	4	,	,	PUNCT
ijassa-1442	468	5	&	&	CCONJ
ijassa-1442	468	6	nkambou	nkambou	PROPN
ijassa-1442	468	7	,	,	PUNCT
ijassa-1442	468	8	r.	r.	PROPN
ijassa-1442	468	9	(	(	PUNCT
ijassa-1442	468	10	2018	2018	NUM
ijassa-1442	468	11	)	)	PUNCT
ijassa-1442	468	12	.	.	PUNCT
ijassa-1442	469	1	improving	improve	VERB
ijassa-1442	469	2	adam	adam	PROPN
ijassa-1442	469	3	optimizer	optimizer	NOUN
ijassa-1442	469	4	.	.	PUNCT
ijassa-1442	470	1	workshop	workshop	NOUN
ijassa-1442	470	2	track	track	NOUN
ijassa-1442	470	3	–	–	PUNCT
ijassa-1442	470	4	iclr	iclr	NOUN
ijassa-1442	470	5	2018	2018	NUM
ijassa-1442	470	6	.	.	PUNCT
ijassa-1442	471	1	vancouver	vancouver	PROPN
ijassa-1442	471	2	,	,	PUNCT
ijassa-1442	471	3	bc	bc	PROPN
ijassa-1442	471	4	,	,	PUNCT
ijassa-1442	471	5	canada	canada	PROPN
ijassa-1442	471	6	.	.	PUNCT
ijassa-1442	472	1	https://doi.org/10.13140/rg.2.2.21344.43528	https://doi.org/10.13140/rg.2.2.21344.43528	PROPN
ijassa-1442	472	2	balancing	balancing	NOUN
ijassa-1442	472	3	accuracy	accuracy	NOUN
ijassa-1442	472	4	,	,	PUNCT
ijassa-1442	472	5	fairness	fairness	NOUN
ijassa-1442	472	6	and	and	CCONJ
ijassa-1442	472	7	privacy	privacy	NOUN
ijassa-1442	472	8	in	in	ADP
ijassa-1442	472	9	machine	machine	NOUN
ijassa-1442	472	10	learning	learning	NOUN
ijassa-1442	472	11	…	…	PUNCT
ijassa-1442	472	12	59	59	NUM
ijassa-1442	472	13	copyright	copyright	NOUN
ijassa-1442	472	14	©	©	PROPN
ijassa-1442	472	15	2023	2023	NUM
ijassa-1442	472	16	assa	assa	NOUN
ijassa-1442	472	17	.	.	PUNCT
ijassa-1442	473	1	adv	adv	PROPN
ijassa-1442	473	2	.	.	PUNCT
ijassa-1442	474	1	in	in	ADP
ijassa-1442	474	2	systems	system	NOUN
ijassa-1442	474	3	science	science	NOUN
ijassa-1442	474	4	and	and	CCONJ
ijassa-1442	474	5	appl	appl	NOUN
ijassa-1442	474	6	.	.	PUNCT
ijassa-1442	475	1	(	(	PUNCT
ijassa-1442	475	2	2023	2023	NUM
ijassa-1442	475	3	)	)	PUNCT
ijassa-1442	475	4	24	24	NUM
ijassa-1442	475	5	.	.	PUNCT
ijassa-1442	475	6	tran	tran	PROPN
ijassa-1442	475	7	,	,	PUNCT
ijassa-1442	475	8	c.	c.	PROPN
ijassa-1442	475	9	,	,	PUNCT
ijassa-1442	475	10	dinh	dinh	PROPN
ijassa-1442	475	11	,	,	PUNCT
ijassa-1442	475	12	m.	m.	NOUN
ijassa-1442	475	13	,	,	PUNCT
ijassa-1442	475	14	&	&	CCONJ
ijassa-1442	475	15	fioretto	fioretto	PROPN
ijassa-1442	475	16	,	,	PUNCT
ijassa-1442	475	17	f.	f.	PROPN
ijassa-1442	475	18	(	(	PUNCT
ijassa-1442	475	19	2021	2021	NUM
ijassa-1442	475	20	)	)	PUNCT
ijassa-1442	475	21	.	.	PUNCT
ijassa-1442	476	1	differentially	differentially	ADV
ijassa-1442	476	2	private	private	ADJ
ijassa-1442	476	3	empirical	empirical	ADJ
ijassa-1442	476	4	risk	risk	NOUN
ijassa-1442	476	5	minimization	minimization	NOUN
ijassa-1442	476	6	under	under	ADP
ijassa-1442	476	7	the	the	DET
ijassa-1442	476	8	fairness	fairness	NOUN
ijassa-1442	476	9	lens	len	NOUN
ijassa-1442	476	10	,	,	PUNCT
ijassa-1442	476	11	advances	advance	NOUN
ijassa-1442	476	12	in	in	ADP
ijassa-1442	476	13	neural	neural	ADJ
ijassa-1442	476	14	information	information	NOUN
ijassa-1442	476	15	processing	processing	NOUN
ijassa-1442	476	16	systems	system	NOUN
ijassa-1442	476	17	(	(	PUNCT
ijassa-1442	476	18	neurips	neurip	NOUN
ijassa-1442	476	19	)	)	PUNCT
ijassa-1442	476	20	,	,	PUNCT
ijassa-1442	476	21	34	34	NUM
ijassa-1442	476	22	,	,	PUNCT
ijassa-1442	476	23	27555–27565	27555–27565	NUM
ijassa-1442	476	24	,	,	PUNCT
ijassa-1442	476	25	https://doi.org/10.48550/arxiv.2106.02674	https://doi.org/10.48550/arxiv.2106.02674	PROPN
ijassa-1442	476	26	25	25	NUM
ijassa-1442	476	27	.	.	PUNCT
ijassa-1442	477	1	tran	tran	PROPN
ijassa-1442	477	2	,	,	PUNCT
ijassa-1442	477	3	c.	c.	NOUN
ijassa-1442	477	4	,	,	PUNCT
ijassa-1442	477	5	fioretto	fioretto	PROPN
ijassa-1442	477	6	,	,	PUNCT
ijassa-1442	477	7	f.	f.	PROPN
ijassa-1442	477	8	,	,	PUNCT
ijassa-1442	477	9	&	&	CCONJ
ijassa-1442	477	10	van	van	PROPN
ijassa-1442	477	11	hentenryck	hentenryck	PROPN
ijassa-1442	477	12	,	,	PUNCT
ijassa-1442	477	13	p.	p.	NOUN
ijassa-1442	477	14	(	(	PUNCT
ijassa-1442	477	15	2021	2021	NUM
ijassa-1442	477	16	)	)	PUNCT
ijassa-1442	477	17	.	.	PUNCT
ijassa-1442	478	1	differentially	differentially	ADV
ijassa-1442	478	2	private	private	ADJ
ijassa-1442	478	3	and	and	CCONJ
ijassa-1442	478	4	fair	fair	ADJ
ijassa-1442	478	5	deep	deep	ADJ
ijassa-1442	478	6	learning	learning	NOUN
ijassa-1442	478	7	:	:	PUNCT
ijassa-1442	478	8	a	a	DET
ijassa-1442	478	9	lagrangian	lagrangian	ADJ
ijassa-1442	478	10	dual	dual	ADJ
ijassa-1442	478	11	approach	approach	NOUN
ijassa-1442	478	12	,	,	PUNCT
ijassa-1442	478	13	proceedings	proceeding	NOUN
ijassa-1442	478	14	of	of	ADP
ijassa-1442	478	15	the	the	DET
ijassa-1442	478	16	aaai	aaai	PROPN
ijassa-1442	478	17	conference	conference	NOUN
ijassa-1442	478	18	on	on	ADP
ijassa-1442	478	19	artificial	artificial	ADJ
ijassa-1442	478	20	intelligence	intelligence	NOUN
ijassa-1442	478	21	,	,	PUNCT
ijassa-1442	478	22	35(11	35(11	NUM
ijassa-1442	478	23	)	)	PUNCT
ijassa-1442	478	24	,	,	PUNCT
ijassa-1442	478	25	9932–9939	9932–9939	NUM
ijassa-1442	478	26	,	,	PUNCT
ijassa-1442	478	27	https://doi.org/10.1609/aaai.v35i11.17193	https://doi.org/10.1609/aaai.v35i11.17193	NOUN
ijassa-1442	478	28	26	26	NUM
ijassa-1442	478	29	.	.	PUNCT
ijassa-1442	479	1	uniyal	uniyal	ADJ
ijassa-1442	479	2	,	,	PUNCT
ijassa-1442	479	3	a.	a.	NOUN
ijassa-1442	479	4	,	,	PUNCT
ijassa-1442	479	5	naidu	naidu	PROPN
ijassa-1442	479	6	,	,	PUNCT
ijassa-1442	479	7	r.	r.	PROPN
ijassa-1442	479	8	,	,	PUNCT
ijassa-1442	479	9	kotti	kotti	PROPN
ijassa-1442	479	10	,	,	PUNCT
ijassa-1442	479	11	s.	s.	PROPN
ijassa-1442	479	12	,	,	PUNCT
ijassa-1442	479	13	singh	singh	PROPN
ijassa-1442	479	14	,	,	PUNCT
ijassa-1442	479	15	s.	s.	PROPN
ijassa-1442	479	16	,	,	PUNCT
ijassa-1442	479	17	kenfack	kenfack	NOUN
ijassa-1442	479	18	,	,	PUNCT
ijassa-1442	479	19	p.	p.	PROPN
ijassa-1442	479	20	j.	j.	PROPN
ijassa-1442	479	21	,	,	PUNCT
ijassa-1442	479	22	&	&	CCONJ
ijassa-1442	479	23	et	et	PROPN
ijassa-1442	479	24	al	al	PROPN
ijassa-1442	479	25	.	.	PROPN
ijassa-1442	479	26	(	(	PUNCT
ijassa-1442	479	27	2022	2022	NUM
ijassa-1442	479	28	)	)	PUNCT
ijassa-1442	479	29	.	.	PUNCT
ijassa-1442	480	1	dp	dp	ADJ
ijassa-1442	480	2	-	-	PUNCT
ijassa-1442	480	3	sgd	sgd	ADJ
ijassa-1442	480	4	vs	vs	NOUN
ijassa-1442	480	5	pate	pate	NOUN
ijassa-1442	480	6	:	:	PUNCT
ijassa-1442	480	7	which	which	PRON
ijassa-1442	480	8	has	have	VERB
ijassa-1442	480	9	less	less	ADJ
ijassa-1442	480	10	disparate	disparate	ADJ
ijassa-1442	480	11	impact	impact	NOUN
ijassa-1442	480	12	on	on	ADP
ijassa-1442	480	13	model	model	NOUN
ijassa-1442	480	14	accuracy	accuracy	NOUN
ijassa-1442	480	15	?	?	PUNCT
ijassa-1442	480	16	.	.	PUNCT
ijassa-1442	481	1	arxiv:2106.12576	arxiv:2106.12576	PROPN
ijassa-1442	481	2	,	,	PUNCT
ijassa-1442	481	3	[	[	X
ijassa-1442	481	4	online	online	X
ijassa-1442	481	5	]	]	X
ijassa-1442	481	6	.	.	PUNCT
ijassa-1442	482	1	available	available	ADJ
ijassa-1442	482	2	:	:	PUNCT
ijassa-1442	482	3	https://arxiv.org/abs/2106.12576	https://arxiv.org/abs/2106.12576	PROPN
ijassa-1442	482	4	27	27	NUM
ijassa-1442	482	5	.	.	PUNCT
ijassa-1442	483	1	verma	verma	PROPN
ijassa-1442	483	2	,	,	PUNCT
ijassa-1442	483	3	s.	s.	PROPN
ijassa-1442	483	4	,	,	PUNCT
ijassa-1442	483	5	&	&	CCONJ
ijassa-1442	483	6	rubin	rubin	PROPN
ijassa-1442	483	7	,	,	PUNCT
ijassa-1442	483	8	j.	j.	PROPN
ijassa-1442	483	9	(	(	PUNCT
ijassa-1442	483	10	2018	2018	NUM
ijassa-1442	483	11	)	)	PUNCT
ijassa-1442	483	12	.	.	PUNCT
ijassa-1442	484	1	fairness	fairness	NOUN
ijassa-1442	484	2	definitions	definition	NOUN
ijassa-1442	484	3	explained	explain	VERB
ijassa-1442	484	4	.	.	PUNCT
ijassa-1442	485	1	proceedings	proceeding	NOUN
ijassa-1442	485	2	of	of	ADP
ijassa-1442	485	3	the	the	DET
ijassa-1442	485	4	2018	2018	NUM
ijassa-1442	485	5	ieee	ieee	NOUN
ijassa-1442	485	6	/	/	SYM
ijassa-1442	485	7	acm	acm	PROPN
ijassa-1442	485	8	international	international	ADJ
ijassa-1442	485	9	workshop	workshop	NOUN
ijassa-1442	485	10	on	on	ADP
ijassa-1442	485	11	software	software	NOUN
ijassa-1442	485	12	fairness	fairness	NOUN
ijassa-1442	485	13	(	(	PUNCT
ijassa-1442	485	14	fairware’18	fairware’18	PROPN
ijassa-1442	485	15	)	)	PUNCT
ijassa-1442	485	16	.	.	PUNCT
ijassa-1442	486	1	ieee	ieee	PROPN
ijassa-1442	486	2	,	,	PUNCT
ijassa-1442	486	3	los	los	PROPN
ijassa-1442	486	4	alamitos	alamitos	PROPN
ijassa-1442	486	5	,	,	PUNCT
ijassa-1442	486	6	ca	ca	NOUN
ijassa-1442	486	7	,	,	PUNCT
ijassa-1442	486	8	1–7	1–7	NUM
ijassa-1442	486	9	,	,	PUNCT
ijassa-1442	486	10	https://doi.org/10.1145/3194770.3194776	https://doi.org/10.1145/3194770.3194776	NOUN
ijassa-1442	486	11	.	.	PUNCT
ijassa-1442	487	1	28	28	NUM
ijassa-1442	487	2	.	.	PUNCT
ijassa-1442	488	1	xie	xie	PROPN
ijassa-1442	488	2	,	,	PUNCT
ijassa-1442	488	3	l.	l.	PROPN
ijassa-1442	488	4	,	,	PUNCT
ijassa-1442	488	5	lin	lin	PROPN
ijassa-1442	488	6	,	,	PUNCT
ijassa-1442	488	7	k.	k.	PROPN
ijassa-1442	488	8	,	,	PUNCT
ijassa-1442	488	9	wang	wang	PROPN
ijassa-1442	488	10	,	,	PUNCT
ijassa-1442	488	11	s.	s.	PROPN
ijassa-1442	488	12	,	,	PUNCT
ijassa-1442	488	13	wang	wang	PROPN
ijassa-1442	488	14	,	,	PUNCT
ijassa-1442	488	15	f.	f.	PROPN
ijassa-1442	488	16	&	&	CCONJ
ijassa-1442	488	17	zhou	zhou	PROPN
ijassa-1442	488	18	,	,	PUNCT
ijassa-1442	488	19	j.	j.	PROPN
ijassa-1442	488	20	(	(	PUNCT
ijassa-1442	488	21	2018	2018	NUM
ijassa-1442	488	22	)	)	PUNCT
ijassa-1442	488	23	.	.	PUNCT
ijassa-1442	489	1	differentially	differentially	ADV
ijassa-1442	489	2	private	private	ADJ
ijassa-1442	489	3	generative	generative	ADJ
ijassa-1442	489	4	adversarial	adversarial	ADJ
ijassa-1442	489	5	network	network	NOUN
ijassa-1442	489	6	.	.	PUNCT
ijassa-1442	490	1	arxiv:1802.06739	arxiv:1802.06739	PROPN
ijassa-1442	490	2	,	,	PUNCT
ijassa-1442	490	3	[	[	X
ijassa-1442	490	4	online	online	X
ijassa-1442	490	5	]	]	X
ijassa-1442	490	6	.	.	PUNCT
ijassa-1442	491	1	available	available	ADJ
ijassa-1442	491	2	:	:	PUNCT
ijassa-1442	491	3	https://arxiv.org/abs/1802.06739	https://arxiv.org/abs/1802.06739	NOUN
ijassa-1442	491	4	29	29	NUM
ijassa-1442	491	5	.	.	PUNCT
ijassa-1442	492	1	zhao	zhao	PROPN
ijassa-1442	492	2	,	,	PUNCT
ijassa-1442	492	3	h.	h.	PROPN
ijassa-1442	492	4	,	,	PUNCT
ijassa-1442	492	5	coston	coston	PROPN
ijassa-1442	492	6	,	,	PUNCT
ijassa-1442	492	7	a.	a.	PROPN
ijassa-1442	492	8	,	,	PUNCT
ijassa-1442	492	9	adel	adel	PROPN
ijassa-1442	492	10	t.	t.	PROPN
ijassa-1442	492	11	,	,	PUNCT
ijassa-1442	492	12	&	&	CCONJ
ijassa-1442	492	13	gordon	gordon	PROPN
ijassa-1442	492	14	,	,	PUNCT
ijassa-1442	492	15	g.j	g.j	PROPN
ijassa-1442	492	16	.	.	PROPN
ijassa-1442	492	17	(	(	PUNCT
ijassa-1442	492	18	2020	2020	NUM
ijassa-1442	492	19	)	)	PUNCT
ijassa-1442	492	20	.	.	PUNCT
ijassa-1442	493	1	conditional	conditional	ADJ
ijassa-1442	493	2	learning	learning	NOUN
ijassa-1442	493	3	of	of	ADP
ijassa-1442	493	4	fair	fair	ADJ
ijassa-1442	493	5	representations	representation	NOUN
ijassa-1442	493	6	.	.	PUNCT
ijassa-1442	494	1	arxiv:1910.07162	arxiv:1910.07162	PROPN
ijassa-1442	494	2	,	,	PUNCT
ijassa-1442	495	1	[	[	X
ijassa-1442	495	2	online	online	X
ijassa-1442	495	3	]	]	X
ijassa-1442	495	4	.	.	PUNCT
ijassa-1442	496	1	available	available	ADJ
ijassa-1442	496	2	:	:	PUNCT
ijassa-1442	496	3	https://arxiv.org/abs/1910.07162	https://arxiv.org/abs/1910.07162	NOUN
ijassa-1442	496	4	30	30	NUM
ijassa-1442	496	5	.	.	PUNCT
ijassa-1442	497	1	smirnova	smirnova	PROPN
ijassa-1442	497	2	g.	g.	PROPN
ijassa-1442	497	3	s.	s.	PROPN
ijassa-1442	497	4	,	,	PUNCT
ijassa-1442	497	5	sabitov	sabitov	PROPN
ijassa-1442	497	6	r.	r.	PROPN
ijassa-1442	497	7	a.	a.	PROPN
ijassa-1442	497	8	,	,	PUNCT
ijassa-1442	497	9	korobkova	korobkova	PROPN
ijassa-1442	497	10	,	,	PUNCT
ijassa-1442	497	11	e.	e.	PROPN
ijassa-1442	497	12	a.	a.	PROPN
ijassa-1442	497	13	,	,	PUNCT
ijassa-1442	497	14	sabitov	sabitov	PROPN
ijassa-1442	497	15	,	,	PUNCT
ijassa-1442	497	16	sh	sh	PROPN
ijassa-1442	497	17	.	.	PROPN
ijassa-1442	497	18	r.	r.	PROPN
ijassa-1442	497	19	(	(	PUNCT
ijassa-1442	497	20	2017	2017	NUM
ijassa-1442	497	21	)	)	PUNCT
ijassa-1442	497	22	.	.	PUNCT
ijassa-1442	498	1	modeling	model	VERB
ijassa-1442	498	2	production	production	NOUN
ijassa-1442	498	3	facility	facility	NOUN
ijassa-1442	498	4	as	as	ADP
ijassa-1442	498	5	a	a	DET
ijassa-1442	498	6	dynamic	dynamic	ADJ
ijassa-1442	498	7	integrated	integrated	ADJ
ijassa-1442	498	8	interacting	interact	VERB
ijassa-1442	498	9	objects	object	NOUN
ijassa-1442	498	10	system	system	NOUN
ijassa-1442	498	11	,	,	PUNCT
ijassa-1442	498	12	procedia	procedia	NOUN
ijassa-1442	498	13	computer	computer	NOUN
ijassa-1442	498	14	science	science	NOUN
ijassa-1442	498	15	,	,	PUNCT
ijassa-1442	498	16	112	112	NUM
ijassa-1442	498	17	,	,	PUNCT
ijassa-1442	498	18	965–970	965–970	NUM
ijassa-1442	498	19	,	,	PUNCT
ijassa-1442	498	20	https://doi.org/10.1016/j.procs.2017.08.136	https://doi.org/10.1016/j.procs.2017.08.136	NOUN