id	sid	tid	token	lemma	pos
bracis-28373	1	1	bayes	bayes	PROPN
bracis-28373	1	2	and	and	CCONJ
bracis-28373	1	3	 	 	SPACE
bracis-28373	1	4	laplace	laplace	NOUN
bracis-28373	1	5	versus	versus	ADP
bracis-28373	1	6	the	the	DET
bracis-28373	1	7	 	 	SPACE
bracis-28373	1	8	world	world	NOUN
bracis-28373	1	9	:	:	PUNCT
bracis-28373	1	10	a	a	DET
bracis-28373	1	11	new	new	ADJ
bracis-28373	1	12	label	label	NOUN
bracis-28373	1	13	attack	attack	NOUN
bracis-28373	1	14	approach	approach	NOUN
bracis-28373	1	15	in	in	ADP
bracis-28373	1	16	 	 	SPACE
bracis-28373	1	17	federated	federated	ADJ
bracis-28373	1	18	environments	environment	NOUN
bracis-28373	1	19	based	base	VERB
bracis-28373	1	20	on	on	ADP
bracis-28373	1	21	 	 	SPACE
bracis-28373	1	22	bayesian	bayesian	NOUN
bracis-28373	1	23	neural	neural	ADJ
bracis-28373	1	24	networks	network	NOUN
bracis-28373	1	25	|	|	ADV
bracis-28373	1	26	springer	springer	NOUN
bracis-28373	1	27	nature	nature	PROPN
bracis-28373	1	28	link	link	PROPN
bracis-28373	1	29	(	(	PUNCT
bracis-28373	1	30	formerly	formerly	ADV
bracis-28373	1	31	springerlink	springerlink	NOUN
bracis-28373	1	32	)	)	PUNCT
bracis-28373	1	33	skip	skip	VERB
bracis-28373	1	34	to	to	ADP
bracis-28373	1	35	main	main	ADJ
bracis-28373	1	36	content	content	NOUN
bracis-28373	1	37	advertisement	advertisement	NOUN
bracis-28373	1	38	log	log	NOUN
bracis-28373	1	39	in	in	ADP
bracis-28373	1	40	menu	menu	NOUN
bracis-28373	1	41	find	find	VERB
bracis-28373	1	42	a	a	DET
bracis-28373	1	43	journal	journal	NOUN
bracis-28373	1	44	publish	publish	VERB
bracis-28373	1	45	with	with	ADP
bracis-28373	1	46	us	we	PRON
bracis-28373	1	47	track	track	VERB
bracis-28373	1	48	your	your	PRON
bracis-28373	1	49	research	research	NOUN
bracis-28373	1	50	search	search	NOUN
bracis-28373	1	51	cart	cart	NOUN
bracis-28373	1	52	home	home	NOUN
bracis-28373	1	53	intelligent	intelligent	ADJ
bracis-28373	1	54	systems	system	NOUN
bracis-28373	1	55	conference	conference	NOUN
bracis-28373	1	56	paper	paper	NOUN
bracis-28373	1	57	bayes	bayes	NOUN
bracis-28373	1	58	and	and	CCONJ
bracis-28373	1	59	 	 	SPACE
bracis-28373	1	60	laplace	laplace	NOUN
bracis-28373	1	61	versus	versus	ADP
bracis-28373	1	62	the	the	DET
bracis-28373	1	63	 	 	SPACE
bracis-28373	1	64	world	world	NOUN
bracis-28373	1	65	:	:	PUNCT
bracis-28373	1	66	a	a	DET
bracis-28373	1	67	new	new	ADJ
bracis-28373	1	68	label	label	NOUN
bracis-28373	1	69	attack	attack	NOUN
bracis-28373	1	70	approach	approach	NOUN
bracis-28373	1	71	in	in	ADP
bracis-28373	1	72	 	 	SPACE
bracis-28373	1	73	federated	federated	ADJ
bracis-28373	1	74	environments	environment	NOUN
bracis-28373	1	75	based	base	VERB
bracis-28373	1	76	on	on	ADP
bracis-28373	1	77	 	 	SPACE
bracis-28373	1	78	bayesian	bayesian	NOUN
bracis-28373	1	79	neural	neural	ADJ
bracis-28373	1	80	networks	network	NOUN
bracis-28373	1	81	conference	conference	NOUN
bracis-28373	1	82	paper	paper	NOUN
bracis-28373	1	83	first	first	ADV
bracis-28373	1	84	online	online	ADV
bracis-28373	1	85	:	:	PUNCT
bracis-28373	1	86	12	12	NUM
bracis-28373	1	87	october	october	NOUN
bracis-28373	1	88	2023	2023	NUM
bracis-28373	1	89	pp	pp	ADP
bracis-28373	1	90	449–463	449–463	NUM
bracis-28373	1	91	cite	cite	VERB
bracis-28373	1	92	this	this	DET
bracis-28373	1	93	conference	conference	NOUN
bracis-28373	1	94	paper	paper	NOUN
bracis-28373	1	95	access	access	NOUN
bracis-28373	1	96	provided	provide	VERB
bracis-28373	1	97	by	by	ADP
bracis-28373	1	98	university	university	PROPN
bracis-28373	1	99	of	of	ADP
bracis-28373	1	100	notre	notre	PROPN
bracis-28373	1	101	dame	dame	PROPN
bracis-28373	1	102	hesburgh	hesburgh	PROPN
bracis-28373	1	103	library	library	PROPN
bracis-28373	1	104	download	download	PROPN
bracis-28373	1	105	book	book	NOUN
bracis-28373	1	106	pdf	pdf	PROPN
bracis-28373	1	107	download	download	NOUN
bracis-28373	1	108	book	book	NOUN
bracis-28373	1	109	epub	epub	PROPN
bracis-28373	1	110	intelligent	intelligent	ADJ
bracis-28373	1	111	systems	system	NOUN
bracis-28373	1	112	(	(	PUNCT
bracis-28373	1	113	bracis	bracis	NOUN
bracis-28373	1	114	2023	2023	NUM
bracis-28373	1	115	)	)	PUNCT
bracis-28373	1	116	bayes	bayes	PROPN
bracis-28373	1	117	and	and	CCONJ
bracis-28373	1	118	 	 	SPACE
bracis-28373	1	119	laplace	laplace	NOUN
bracis-28373	1	120	versus	versus	ADP
bracis-28373	1	121	the	the	DET
bracis-28373	1	122	 	 	SPACE
bracis-28373	1	123	world	world	NOUN
bracis-28373	1	124	:	:	PUNCT
bracis-28373	1	125	a	a	DET
bracis-28373	1	126	new	new	ADJ
bracis-28373	1	127	label	label	NOUN
bracis-28373	1	128	attack	attack	NOUN
bracis-28373	1	129	approach	approach	NOUN
bracis-28373	1	130	in	in	ADP
bracis-28373	1	131	 	 	SPACE
bracis-28373	1	132	federated	federated	ADJ
bracis-28373	1	133	environments	environment	NOUN
bracis-28373	1	134	based	base	VERB
bracis-28373	1	135	on	on	ADP
bracis-28373	1	136	 	 	SPACE
bracis-28373	1	137	bayesian	bayesian	NOUN
bracis-28373	1	138	neural	neural	ADJ
bracis-28373	1	139	networks	network	NOUN
bracis-28373	1	140	download	download	NOUN
bracis-28373	1	141	book	book	NOUN
bracis-28373	1	142	pdf	pdf	PROPN
bracis-28373	1	143	download	download	NOUN
bracis-28373	1	144	book	book	NOUN
bracis-28373	1	145	epub	epub	PROPN
bracis-28373	1	146	pedro	pedro	PROPN
bracis-28373	1	147	h.	h.	PROPN
bracis-28373	1	148	barros9	barros9	PROPN
bracis-28373	1	149	,	,	PUNCT
bracis-28373	1	150	fabricio	fabricio	PROPN
bracis-28373	1	151	murai10	murai10	PROPN
bracis-28373	1	152	&	&	CCONJ
bracis-28373	1	153	heitor	heitor	PROPN
bracis-28373	1	154	s.	s.	PROPN
bracis-28373	1	155	ramos9	ramos9	PROPN
bracis-28373	1	156	  	  	SPACE
bracis-28373	1	157	part	part	NOUN
bracis-28373	1	158	of	of	ADP
bracis-28373	1	159	the	the	DET
bracis-28373	1	160	book	book	NOUN
bracis-28373	1	161	series	series	NOUN
bracis-28373	1	162	:	:	PUNCT
bracis-28373	1	163	lecture	lecture	NOUN
bracis-28373	1	164	notes	note	NOUN
bracis-28373	1	165	in	in	ADP
bracis-28373	1	166	computer	computer	NOUN
bracis-28373	1	167	science	science	NOUN
bracis-28373	1	168	(	(	PUNCT
bracis-28373	1	169	(	(	PUNCT
bracis-28373	1	170	lnai	lnai	ADJ
bracis-28373	1	171	,	,	PUNCT
bracis-28373	1	172	volume	volume	NOUN
bracis-28373	1	173	14195	14195	NUM
bracis-28373	1	174	)	)	PUNCT
bracis-28373	1	175	)	)	PUNCT
bracis-28373	1	176	included	include	VERB
bracis-28373	1	177	in	in	ADP
bracis-28373	1	178	the	the	DET
bracis-28373	1	179	following	follow	VERB
bracis-28373	1	180	conference	conference	NOUN
bracis-28373	1	181	series	series	NOUN
bracis-28373	1	182	:	:	PUNCT
bracis-28373	1	183	brazilian	brazilian	ADJ
bracis-28373	1	184	conference	conference	NOUN
bracis-28373	1	185	on	on	ADP
bracis-28373	1	186	intelligent	intelligent	ADJ
bracis-28373	1	187	systems	system	NOUN
bracis-28373	1	188	550	550	NUM
bracis-28373	1	189	accesses	access	NOUN
bracis-28373	1	190	abstract	abstract	ADJ
bracis-28373	1	191	federated	federated	ADJ
bracis-28373	1	192	learning	learning	NOUN
bracis-28373	1	193	(	(	PUNCT
bracis-28373	1	194	fl	fl	NOUN
bracis-28373	1	195	)	)	PUNCT
bracis-28373	1	196	is	be	AUX
bracis-28373	1	197	a	a	DET
bracis-28373	1	198	decentralized	decentralized	ADJ
bracis-28373	1	199	machine	machine	NOUN
bracis-28373	1	200	learning	learn	VERB
bracis-28373	1	201	approach	approach	NOUN
bracis-28373	1	202	developed	develop	VERB
bracis-28373	1	203	to	to	PART
bracis-28373	1	204	ensure	ensure	VERB
bracis-28373	1	205	that	that	SCONJ
bracis-28373	1	206	training	training	NOUN
bracis-28373	1	207	data	datum	NOUN
bracis-28373	1	208	remains	remain	VERB
bracis-28373	1	209	on	on	ADP
bracis-28373	1	210	personal	personal	ADJ
bracis-28373	1	211	devices	device	NOUN
bracis-28373	1	212	,	,	PUNCT
bracis-28373	1	213	preserving	preserve	VERB
bracis-28373	1	214	data	datum	NOUN
bracis-28373	1	215	privacy	privacy	NOUN
bracis-28373	1	216	.	.	PUNCT
bracis-28373	2	1	however	however	ADV
bracis-28373	2	2	,	,	PUNCT
bracis-28373	2	3	the	the	DET
bracis-28373	2	4	distributed	distribute	VERB
bracis-28373	2	5	nature	nature	NOUN
bracis-28373	2	6	of	of	ADP
bracis-28373	2	7	fl	fl	PRON
bracis-28373	2	8	environments	environment	NOUN
bracis-28373	2	9	makes	make	VERB
bracis-28373	2	10	defense	defense	NOUN
bracis-28373	2	11	against	against	ADP
bracis-28373	2	12	malicious	malicious	ADJ
bracis-28373	2	13	attacks	attack	NOUN
bracis-28373	2	14	a	a	DET
bracis-28373	2	15	challenging	challenging	ADJ
bracis-28373	2	16	task	task	NOUN
bracis-28373	2	17	.	.	PUNCT
bracis-28373	3	1	this	this	DET
bracis-28373	3	2	work	work	NOUN
bracis-28373	3	3	proposes	propose	VERB
bracis-28373	3	4	a	a	DET
bracis-28373	3	5	new	new	ADJ
bracis-28373	3	6	attack	attack	NOUN
bracis-28373	3	7	approach	approach	NOUN
bracis-28373	3	8	to	to	ADP
bracis-28373	3	9	poisoning	poisoning	NOUN
bracis-28373	3	10	labels	label	NOUN
bracis-28373	3	11	using	use	VERB
bracis-28373	3	12	bayesian	bayesian	NOUN
bracis-28373	3	13	neural	neural	ADJ
bracis-28373	3	14	networks	network	NOUN
bracis-28373	3	15	in	in	ADP
bracis-28373	3	16	federated	federated	ADJ
bracis-28373	3	17	environments	environment	NOUN
bracis-28373	3	18	.	.	PUNCT
bracis-28373	4	1	the	the	DET
bracis-28373	4	2	hypothesis	hypothesis	NOUN
bracis-28373	4	3	is	be	AUX
bracis-28373	4	4	that	that	SCONJ
bracis-28373	4	5	a	a	DET
bracis-28373	4	6	label	label	NOUN
bracis-28373	4	7	poisoning	poisoning	NOUN
bracis-28373	4	8	attack	attack	NOUN
bracis-28373	4	9	model	model	NOUN
bracis-28373	4	10	trained	train	VERB
bracis-28373	4	11	with	with	ADP
bracis-28373	4	12	the	the	DET
bracis-28373	4	13	marginal	marginal	ADJ
bracis-28373	4	14	likelihood	likelihood	NOUN
bracis-28373	4	15	loss	loss	NOUN
bracis-28373	4	16	can	can	AUX
bracis-28373	4	17	generate	generate	VERB
bracis-28373	4	18	a	a	DET
bracis-28373	4	19	less	less	ADV
bracis-28373	4	20	complex	complex	ADJ
bracis-28373	4	21	poisoned	poison	VERB
bracis-28373	4	22	model	model	NOUN
bracis-28373	4	23	,	,	PUNCT
bracis-28373	4	24	making	make	VERB
bracis-28373	4	25	it	it	PRON
bracis-28373	4	26	difficult	difficult	ADJ
bracis-28373	4	27	to	to	PART
bracis-28373	4	28	detect	detect	VERB
bracis-28373	4	29	attacks	attack	NOUN
bracis-28373	4	30	.	.	PUNCT
bracis-28373	5	1	we	we	PRON
bracis-28373	5	2	present	present	VERB
bracis-28373	5	3	experimental	experimental	ADJ
bracis-28373	5	4	results	result	NOUN
bracis-28373	5	5	demonstrating	demonstrate	VERB
bracis-28373	5	6	the	the	DET
bracis-28373	5	7	proposed	propose	VERB
bracis-28373	5	8	approach	approach	NOUN
bracis-28373	5	9	’s	’s	PART
bracis-28373	5	10	effectiveness	effectiveness	NOUN
bracis-28373	5	11	in	in	ADP
bracis-28373	5	12	generating	generate	VERB
bracis-28373	5	13	poisoned	poison	VERB
bracis-28373	5	14	models	model	NOUN
bracis-28373	5	15	in	in	ADP
bracis-28373	5	16	federated	federated	ADJ
bracis-28373	5	17	environments	environment	NOUN
bracis-28373	5	18	.	.	PUNCT
bracis-28373	6	1	additionally	additionally	ADV
bracis-28373	6	2	,	,	PUNCT
bracis-28373	6	3	we	we	PRON
bracis-28373	6	4	analyze	analyze	VERB
bracis-28373	6	5	the	the	DET
bracis-28373	6	6	performance	performance	NOUN
bracis-28373	6	7	of	of	ADP
bracis-28373	6	8	various	various	ADJ
bracis-28373	6	9	defense	defense	NOUN
bracis-28373	6	10	mechanisms	mechanism	NOUN
bracis-28373	6	11	against	against	ADP
bracis-28373	6	12	different	different	ADJ
bracis-28373	6	13	attack	attack	NOUN
bracis-28373	6	14	proposals	proposal	NOUN
bracis-28373	6	15	,	,	PUNCT
bracis-28373	6	16	evaluating	evaluate	VERB
bracis-28373	6	17	accuracy	accuracy	NOUN
bracis-28373	6	18	,	,	PUNCT
bracis-28373	6	19	precision	precision	NOUN
bracis-28373	6	20	,	,	PUNCT
bracis-28373	6	21	recall	recall	NOUN
bracis-28373	6	22	,	,	PUNCT
bracis-28373	6	23	and	and	CCONJ
bracis-28373	6	24	f1	f1	NOUN
bracis-28373	6	25	-	-	PUNCT
bracis-28373	6	26	score	score	NOUN
bracis-28373	6	27	.	.	PUNCT
bracis-28373	7	1	the	the	DET
bracis-28373	7	2	results	result	NOUN
bracis-28373	7	3	show	show	VERB
bracis-28373	7	4	that	that	SCONJ
bracis-28373	7	5	our	our	PRON
bracis-28373	7	6	proposed	propose	VERB
bracis-28373	7	7	attack	attack	NOUN
bracis-28373	7	8	mechanism	mechanism	NOUN
bracis-28373	7	9	is	be	AUX
bracis-28373	7	10	harder	hard	ADJ
bracis-28373	7	11	to	to	PART
bracis-28373	7	12	defend	defend	VERB
bracis-28373	7	13	when	when	SCONJ
bracis-28373	7	14	we	we	PRON
bracis-28373	7	15	adopt	adopt	VERB
bracis-28373	7	16	existing	exist	VERB
bracis-28373	7	17	defense	defense	NOUN
bracis-28373	7	18	mechanisms	mechanism	NOUN
bracis-28373	7	19	against	against	ADP
bracis-28373	7	20	label	label	NOUN
bracis-28373	7	21	poisoning	poisoning	NOUN
bracis-28373	7	22	attacks	attack	NOUN
bracis-28373	7	23	in	in	ADP
bracis-28373	7	24	fl	fl	PROPN
bracis-28373	7	25	,	,	PUNCT
bracis-28373	7	26	showing	show	VERB
bracis-28373	7	27	a	a	DET
bracis-28373	7	28	difference	difference	NOUN
bracis-28373	7	29	of	of	ADP
bracis-28373	7	30	18.48	18.48	NUM
bracis-28373	7	31	%	%	NOUN
bracis-28373	7	32	for	for	ADP
bracis-28373	7	33	accuracy	accuracy	NOUN
bracis-28373	7	34	compared	compare	VERB
bracis-28373	7	35	to	to	ADP
bracis-28373	7	36	the	the	DET
bracis-28373	7	37	approach	approach	NOUN
bracis-28373	7	38	without	without	ADP
bracis-28373	7	39	malicious	malicious	ADJ
bracis-28373	7	40	clients	client	NOUN
bracis-28373	7	41	.	.	PUNCT
bracis-28373	8	1	access	access	NOUN
bracis-28373	8	2	provided	provide	VERB
bracis-28373	8	3	by	by	ADP
bracis-28373	8	4	university	university	PROPN
bracis-28373	8	5	of	of	ADP
bracis-28373	8	6	notre	notre	PROPN
bracis-28373	8	7	dame	dame	PROPN
bracis-28373	8	8	hesburgh	hesburgh	PROPN
bracis-28373	8	9	library	library	PROPN
bracis-28373	8	10	.	.	PUNCT
bracis-28373	9	1	download	download	PROPN
bracis-28373	9	2	conference	conference	NOUN
bracis-28373	9	3	paper	paper	NOUN
bracis-28373	9	4	pdf	pdf	NOUN
bracis-28373	9	5	similar	similar	ADJ
bracis-28373	9	6	content	content	NOUN
bracis-28373	9	7	being	be	AUX
bracis-28373	9	8	viewed	view	VERB
bracis-28373	9	9	by	by	ADP
bracis-28373	9	10	others	other	NOUN
bracis-28373	9	11	data	datum	NOUN
bracis-28373	9	12	poisoning	poisoning	NOUN
bracis-28373	9	13	attacks	attack	NOUN
bracis-28373	9	14	against	against	ADP
bracis-28373	9	15	federated	federated	ADJ
bracis-28373	9	16	learning	learning	NOUN
bracis-28373	9	17	systems	system	NOUN
bracis-28373	9	18	chapter	chapter	NOUN
bracis-28373	9	19	©	©	PROPN
bracis-28373	9	20	2020	2020	NUM
bracis-28373	9	21	a	a	DET
bracis-28373	9	22	defense	defense	NOUN
bracis-28373	9	23	method	method	NOUN
bracis-28373	9	24	against	against	ADP
bracis-28373	9	25	multi	multi	ADJ
bracis-28373	9	26	-	-	ADJ
bracis-28373	9	27	label	label	ADJ
bracis-28373	9	28	poisoning	poisoning	NOUN
bracis-28373	9	29	attacks	attack	NOUN
bracis-28373	9	30	in	in	ADP
bracis-28373	9	31	federated	federated	ADJ
bracis-28373	9	32	learning	learn	VERB
bracis-28373	9	33	article	article	NOUN
bracis-28373	9	34	open	open	ADJ
bracis-28373	9	35	access	access	NOUN
bracis-28373	9	36	19	19	NUM
bracis-28373	9	37	july	july	PROPN
bracis-28373	9	38	2025	2025	NUM
bracis-28373	9	39	mitigating	mitigate	VERB
bracis-28373	9	40	model	model	NOUN
bracis-28373	9	41	poisoning	poisoning	NOUN
bracis-28373	9	42	attacks	attack	NOUN
bracis-28373	9	43	in	in	ADP
bracis-28373	9	44	 	 	SPACE
bracis-28373	9	45	federated	federated	ADJ
bracis-28373	9	46	learning	learning	NOUN
bracis-28373	9	47	:	:	PUNCT
bracis-28373	9	48	a	a	DET
bracis-28373	9	49	comprehensive	comprehensive	ADJ
bracis-28373	9	50	approach	approach	NOUN
bracis-28373	9	51	chapter	chapter	NOUN
bracis-28373	9	52	©	©	PROPN
bracis-28373	9	53	2025	2025	NUM
bracis-28373	9	54	explore	explore	VERB
bracis-28373	9	55	related	relate	VERB
bracis-28373	9	56	subjects	subject	NOUN
bracis-28373	9	57	discover	discover	VERB
bracis-28373	9	58	the	the	DET
bracis-28373	9	59	latest	late	ADJ
bracis-28373	9	60	articles	article	NOUN
bracis-28373	9	61	,	,	PUNCT
bracis-28373	9	62	books	book	NOUN
bracis-28373	9	63	and	and	CCONJ
bracis-28373	9	64	news	news	NOUN
bracis-28373	9	65	in	in	ADP
bracis-28373	9	66	related	related	ADJ
bracis-28373	9	67	subjects	subject	NOUN
bracis-28373	9	68	,	,	PUNCT
bracis-28373	9	69	suggested	suggest	VERB
bracis-28373	9	70	using	use	VERB
bracis-28373	9	71	machine	machine	NOUN
bracis-28373	9	72	learning	learning	NOUN
bracis-28373	9	73	.	.	PUNCT
bracis-28373	10	1	bayesian	bayesian	NOUN
bracis-28373	10	2	inference	inference	NOUN
bracis-28373	10	3	bayesian	bayesian	NOUN
bracis-28373	10	4	network	network	NOUN
bracis-28373	10	5	cybercrime	cybercrime	NOUN
bracis-28373	10	6	immune	immune	ADJ
bracis-28373	10	7	evasion	evasion	NOUN
bracis-28373	10	8	machine	machine	NOUN
bracis-28373	10	9	learning	learn	VERB
bracis-28373	10	10	neural	neural	ADJ
bracis-28373	10	11	encoding	encode	VERB
bracis-28373	10	12	1	1	NUM
bracis-28373	10	13	introdution	introdution	NOUN
bracis-28373	10	14	the	the	DET
bracis-28373	10	15	internet	internet	NOUN
bracis-28373	10	16	of	of	ADP
bracis-28373	10	17	things	thing	NOUN
bracis-28373	10	18	(	(	PUNCT
bracis-28373	10	19	iot	iot	NOUN
bracis-28373	10	20	)	)	PUNCT
bracis-28373	10	21	has	have	AUX
bracis-28373	10	22	become	become	VERB
bracis-28373	10	23	increasingly	increasingly	ADV
bracis-28373	10	24	impactful	impactful	ADJ
bracis-28373	10	25	,	,	PUNCT
bracis-28373	10	26	empowering	empower	VERB
bracis-28373	10	27	diverse	diverse	ADJ
bracis-28373	10	28	applications	application	NOUN
bracis-28373	10	29	 	 	SPACE
bracis-28373	11	1	[	[	X
bracis-28373	11	2	14	14	NUM
bracis-28373	11	3	]	]	PUNCT
bracis-28373	11	4	.	.	PUNCT
bracis-28373	12	1	approximately	approximately	ADV
bracis-28373	12	2	5.8	5.8	NUM
bracis-28373	12	3	billion	billion	NUM
bracis-28373	12	4	iot	iot	NOUN
bracis-28373	12	5	devices	device	NOUN
bracis-28373	12	6	are	be	AUX
bracis-28373	12	7	estimated	estimate	VERB
bracis-28373	12	8	to	to	PART
bracis-28373	12	9	be	be	AUX
bracis-28373	12	10	in	in	ADP
bracis-28373	12	11	use	use	NOUN
bracis-28373	12	12	this	this	DET
bracis-28373	12	13	year	year	NOUN
bracis-28373	12	14	 	 	SPACE
bracis-28373	13	1	[	[	X
bracis-28373	13	2	6	6	NUM
bracis-28373	13	3	]	]	PUNCT
bracis-28373	13	4	.	.	PUNCT
bracis-28373	14	1	moreover	moreover	ADV
bracis-28373	14	2	,	,	PUNCT
bracis-28373	14	3	privacy	privacy	NOUN
bracis-28373	14	4	issues	issue	NOUN
bracis-28373	14	5	are	be	AUX
bracis-28373	14	6	becoming	become	VERB
bracis-28373	14	7	increasingly	increasingly	ADV
bracis-28373	14	8	relevant	relevant	ADJ
bracis-28373	14	9	for	for	ADP
bracis-28373	14	10	distributed	distributed	ADJ
bracis-28373	14	11	applications	application	NOUN
bracis-28373	14	12	,	,	PUNCT
bracis-28373	14	13	as	as	SCONJ
bracis-28373	14	14	seen	see	VERB
bracis-28373	14	15	recently	recently	ADV
bracis-28373	14	16	in	in	ADP
bracis-28373	14	17	general	general	ADJ
bracis-28373	14	18	data	datum	NOUN
bracis-28373	14	19	protection	protection	NOUN
bracis-28373	14	20	regulation	regulation	NOUN
bracis-28373	14	21	(	(	PUNCT
bracis-28373	14	22	gdpr	gdpr	NOUN
bracis-28373	14	23	)	)	PUNCT
bracis-28373	14	24	.	.	PUNCT
bracis-28373	15	1	a	a	DET
bracis-28373	15	2	decentralized	decentralize	VERB
bracis-28373	15	3	machine	machine	NOUN
bracis-28373	15	4	learning	learn	VERB
bracis-28373	15	5	approach	approach	NOUN
bracis-28373	15	6	called	call	VERB
bracis-28373	15	7	federated	federated	ADJ
bracis-28373	15	8	learning	learning	NOUN
bracis-28373	15	9	(	(	PUNCT
bracis-28373	15	10	fl	fl	NOUN
bracis-28373	15	11	)	)	PUNCT
bracis-28373	15	12	was	be	AUX
bracis-28373	15	13	proposed	propose	VERB
bracis-28373	15	14	to	to	PART
bracis-28373	15	15	guarantee	guarantee	VERB
bracis-28373	15	16	that	that	SCONJ
bracis-28373	15	17	training	training	NOUN
bracis-28373	15	18	data	datum	NOUN
bracis-28373	15	19	remains	remain	VERB
bracis-28373	15	20	on	on	ADP
bracis-28373	15	21	personal	personal	ADJ
bracis-28373	15	22	devices	device	NOUN
bracis-28373	15	23	and	and	CCONJ
bracis-28373	15	24	facilitates	facilitate	VERB
bracis-28373	15	25	complex	complex	ADJ
bracis-28373	15	26	models	model	NOUN
bracis-28373	15	27	of	of	ADP
bracis-28373	15	28	collaborative	collaborative	ADJ
bracis-28373	15	29	machine	machine	NOUN
bracis-28373	15	30	learning	learn	VERB
bracis-28373	15	31	on	on	ADP
bracis-28373	15	32	distributed	distribute	VERB
bracis-28373	15	33	devices	device	NOUN
bracis-28373	15	34	.	.	PUNCT
bracis-28373	16	1	the	the	DET
bracis-28373	16	2	training	training	NOUN
bracis-28373	16	3	of	of	ADP
bracis-28373	16	4	a	a	DET
bracis-28373	16	5	federated	federated	ADJ
bracis-28373	16	6	model	model	NOUN
bracis-28373	16	7	is	be	AUX
bracis-28373	16	8	performed	perform	VERB
bracis-28373	16	9	in	in	ADP
bracis-28373	16	10	a	a	DET
bracis-28373	16	11	distributed	distribute	VERB
bracis-28373	16	12	fashion	fashion	NOUN
bracis-28373	16	13	where	where	SCONJ
bracis-28373	16	14	data	datum	NOUN
bracis-28373	16	15	remains	remain	VERB
bracis-28373	16	16	on	on	ADP
bracis-28373	16	17	users	user	NOUN
bracis-28373	16	18	’	'	PUNCT
bracis-28373	16	19	local	local	ADJ
bracis-28373	16	20	devices	device	NOUN
bracis-28373	16	21	while	while	SCONJ
bracis-28373	16	22	the	the	DET
bracis-28373	16	23	model	model	NOUN
bracis-28373	16	24	is	be	AUX
bracis-28373	16	25	updated	update	VERB
bracis-28373	16	26	globally	globally	ADV
bracis-28373	16	27	 	 	SPACE
bracis-28373	16	28	[	[	X
bracis-28373	16	29	15	15	NUM
bracis-28373	16	30	]	]	PUNCT
bracis-28373	16	31	.	.	PUNCT
bracis-28373	17	1	during	during	ADP
bracis-28373	17	2	training	training	NOUN
bracis-28373	17	3	,	,	PUNCT
bracis-28373	17	4	the	the	DET
bracis-28373	17	5	global	global	ADJ
bracis-28373	17	6	model	model	NOUN
bracis-28373	17	7	is	be	AUX
bracis-28373	17	8	sent	send	VERB
bracis-28373	17	9	to	to	ADP
bracis-28373	17	10	users	user	NOUN
bracis-28373	17	11	’	'	PUNCT
bracis-28373	17	12	devices	device	NOUN
bracis-28373	17	13	,	,	PUNCT
bracis-28373	17	14	which	which	PRON
bracis-28373	17	15	evaluate	evaluate	VERB
bracis-28373	17	16	the	the	DET
bracis-28373	17	17	model	model	NOUN
bracis-28373	17	18	with	with	ADP
bracis-28373	17	19	local	local	ADJ
bracis-28373	17	20	estimates	estimate	NOUN
bracis-28373	17	21	.	.	PUNCT
bracis-28373	18	1	furthermore	furthermore	ADV
bracis-28373	18	2	,	,	PUNCT
bracis-28373	18	3	local	local	ADJ
bracis-28373	18	4	updates	update	NOUN
bracis-28373	18	5	are	be	AUX
bracis-28373	18	6	sent	send	VERB
bracis-28373	18	7	back	back	ADV
bracis-28373	18	8	to	to	ADP
bracis-28373	18	9	the	the	DET
bracis-28373	18	10	server	server	NOUN
bracis-28373	18	11	,	,	PUNCT
bracis-28373	18	12	aggregating	aggregate	VERB
bracis-28373	18	13	them	they	PRON
bracis-28373	18	14	into	into	ADP
bracis-28373	18	15	a	a	DET
bracis-28373	18	16	central	central	ADJ
bracis-28373	18	17	model	model	NOUN
bracis-28373	18	18	.	.	PUNCT
bracis-28373	19	1	data	datum	NOUN
bracis-28373	19	2	privacy	privacy	NOUN
bracis-28373	19	3	tends	tend	VERB
bracis-28373	19	4	to	to	PART
bracis-28373	19	5	be	be	AUX
bracis-28373	19	6	preserved	preserve	VERB
bracis-28373	19	7	as	as	SCONJ
bracis-28373	19	8	no	no	DET
bracis-28373	19	9	actual	actual	ADJ
bracis-28373	19	10	data	datum	NOUN
bracis-28373	19	11	is	be	AUX
bracis-28373	19	12	shared	share	VERB
bracis-28373	19	13	,	,	PUNCT
bracis-28373	19	14	only	only	ADJ
bracis-28373	19	15	model	model	NOUN
bracis-28373	19	16	updates	update	VERB
bracis-28373	19	17	.	.	PUNCT
bracis-28373	20	1	with	with	ADP
bracis-28373	20	2	the	the	DET
bracis-28373	20	3	increasing	increase	VERB
bracis-28373	20	4	use	use	NOUN
bracis-28373	20	5	of	of	ADP
bracis-28373	20	6	machine	machine	NOUN
bracis-28373	20	7	learning	learn	VERB
bracis-28373	20	8	algorithms	algorithm	NOUN
bracis-28373	20	9	in	in	ADP
bracis-28373	20	10	federated	federated	ADJ
bracis-28373	20	11	environments	environment	NOUN
bracis-28373	20	12	,	,	PUNCT
bracis-28373	20	13	it	it	PRON
bracis-28373	20	14	is	be	AUX
bracis-28373	20	15	necessary	necessary	ADJ
bracis-28373	20	16	to	to	PART
bracis-28373	20	17	ensure	ensure	VERB
bracis-28373	20	18	user	user	NOUN
bracis-28373	20	19	data	data	PROPN
bracis-28373	20	20	privacy	privacy	NOUN
bracis-28373	20	21	and	and	CCONJ
bracis-28373	20	22	security	security	NOUN
bracis-28373	20	23	and	and	CCONJ
bracis-28373	20	24	the	the	DET
bracis-28373	20	25	constructed	construct	VERB
bracis-28373	20	26	models	model	NOUN
bracis-28373	20	27	’	'	PUNCT
bracis-28373	20	28	reliability	reliability	NOUN
bracis-28373	20	29	.	.	PUNCT
bracis-28373	21	1	however	however	ADV
bracis-28373	21	2	,	,	PUNCT
bracis-28373	21	3	the	the	DET
bracis-28373	21	4	distributed	distribute	VERB
bracis-28373	21	5	nature	nature	NOUN
bracis-28373	21	6	of	of	ADP
bracis-28373	21	7	these	these	DET
bracis-28373	21	8	environments	environment	NOUN
bracis-28373	21	9	and	and	CCONJ
bracis-28373	21	10	the	the	DET
bracis-28373	21	11	heterogeneity	heterogeneity	NOUN
bracis-28373	21	12	of	of	ADP
bracis-28373	21	13	user	user	NOUN
bracis-28373	21	14	data	datum	NOUN
bracis-28373	21	15	make	make	VERB
bracis-28373	21	16	this	this	DET
bracis-28373	21	17	process	process	NOUN
bracis-28373	21	18	challenging	challenge	VERB
bracis-28373	21	19	.	.	PUNCT
bracis-28373	22	1	furthermore	furthermore	ADV
bracis-28373	22	2	,	,	PUNCT
bracis-28373	22	3	these	these	DET
bracis-28373	22	4	techniques	technique	NOUN
bracis-28373	22	5	still	still	ADV
bracis-28373	22	6	present	present	ADJ
bracis-28373	22	7	vulnerabilities	vulnerability	NOUN
bracis-28373	22	8	,	,	PUNCT
bracis-28373	22	9	as	as	SCONJ
bracis-28373	22	10	the	the	DET
bracis-28373	22	11	model	model	NOUN
bracis-28373	22	12	is	be	AUX
bracis-28373	22	13	trained	train	VERB
bracis-28373	22	14	based	base	VERB
bracis-28373	22	15	on	on	ADP
bracis-28373	22	16	data	datum	NOUN
bracis-28373	22	17	from	from	ADP
bracis-28373	22	18	multiple	multiple	ADJ
bracis-28373	22	19	users	user	NOUN
bracis-28373	22	20	,	,	PUNCT
bracis-28373	22	21	including	include	VERB
bracis-28373	22	22	potential	potential	ADJ
bracis-28373	22	23	attackers	attacker	NOUN
bracis-28373	22	24	.	.	PUNCT
bracis-28373	23	1	developing	develop	VERB
bracis-28373	23	2	defense	defense	NOUN
bracis-28373	23	3	strategies	strategy	NOUN
bracis-28373	23	4	against	against	ADP
bracis-28373	23	5	malicious	malicious	ADJ
bracis-28373	23	6	attacks	attack	NOUN
bracis-28373	23	7	in	in	ADP
bracis-28373	23	8	federated	federated	ADJ
bracis-28373	23	9	environments	environment	NOUN
bracis-28373	23	10	becomes	become	VERB
bracis-28373	23	11	crucial	crucial	ADJ
bracis-28373	23	12	to	to	PART
bracis-28373	23	13	ensure	ensure	VERB
bracis-28373	23	14	the	the	DET
bracis-28373	23	15	security	security	NOUN
bracis-28373	23	16	and	and	CCONJ
bracis-28373	23	17	privacy	privacy	NOUN
bracis-28373	23	18	of	of	ADP
bracis-28373	23	19	users	user	NOUN
bracis-28373	23	20	.	.	PUNCT
bracis-28373	24	1	a	a	DET
bracis-28373	24	2	promising	promising	ADJ
bracis-28373	24	3	approach	approach	NOUN
bracis-28373	24	4	to	to	ADP
bracis-28373	24	5	this	this	DET
bracis-28373	24	6	issue	issue	NOUN
bracis-28373	24	7	is	be	AUX
bracis-28373	24	8	the	the	DET
bracis-28373	24	9	construction	construction	NOUN
bracis-28373	24	10	of	of	ADP
bracis-28373	24	11	malicious	malicious	ADJ
bracis-28373	24	12	models	model	NOUN
bracis-28373	24	13	that	that	PRON
bracis-28373	24	14	can	can	AUX
bracis-28373	24	15	be	be	AUX
bracis-28373	24	16	used	use	VERB
bracis-28373	24	17	to	to	PART
bracis-28373	24	18	attack	attack	VERB
bracis-28373	24	19	other	other	ADJ
bracis-28373	24	20	models	model	NOUN
bracis-28373	24	21	and	and	CCONJ
bracis-28373	24	22	,	,	PUNCT
bracis-28373	24	23	therefore	therefore	ADV
bracis-28373	24	24	,	,	PUNCT
bracis-28373	24	25	test	test	VERB
bracis-28373	24	26	the	the	DET
bracis-28373	24	27	robustness	robustness	NOUN
bracis-28373	24	28	of	of	ADP
bracis-28373	24	29	the	the	DET
bracis-28373	24	30	federation	federation	NOUN
bracis-28373	24	31	.	.	PUNCT
bracis-28373	25	1	furthermore	furthermore	ADV
bracis-28373	25	2	,	,	PUNCT
bracis-28373	25	3	these	these	DET
bracis-28373	25	4	malicious	malicious	ADJ
bracis-28373	25	5	models	model	NOUN
bracis-28373	25	6	are	be	AUX
bracis-28373	25	7	built	build	VERB
bracis-28373	25	8	to	to	PART
bracis-28373	25	9	exploit	exploit	VERB
bracis-28373	25	10	the	the	DET
bracis-28373	25	11	vulnerabilities	vulnerability	NOUN
bracis-28373	25	12	of	of	ADP
bracis-28373	25	13	models	model	NOUN
bracis-28373	25	14	in	in	ADP
bracis-28373	25	15	federated	federated	ADJ
bracis-28373	25	16	environments	environment	NOUN
bracis-28373	25	17	,	,	PUNCT
bracis-28373	25	18	making	make	VERB
bracis-28373	25	19	them	they	PRON
bracis-28373	25	20	helpful	helpful	ADJ
bracis-28373	25	21	in	in	ADP
bracis-28373	25	22	evaluating	evaluate	VERB
bracis-28373	25	23	the	the	DET
bracis-28373	25	24	effectiveness	effectiveness	NOUN
bracis-28373	25	25	of	of	ADP
bracis-28373	25	26	defense	defense	NOUN
bracis-28373	25	27	techniques	technique	NOUN
bracis-28373	25	28	.	.	PUNCT
bracis-28373	26	1	in	in	ADP
bracis-28373	26	2	federated	federated	ADJ
bracis-28373	26	3	learning	learning	NOUN
bracis-28373	26	4	,	,	PUNCT
bracis-28373	26	5	neural	neural	ADJ
bracis-28373	26	6	networks	network	NOUN
bracis-28373	26	7	are	be	AUX
bracis-28373	26	8	commonly	commonly	ADV
bracis-28373	26	9	used	use	VERB
bracis-28373	26	10	as	as	ADP
bracis-28373	26	11	a	a	DET
bracis-28373	26	12	machine	machine	NOUN
bracis-28373	26	13	learning	learn	VERB
bracis-28373	26	14	model	model	NOUN
bracis-28373	26	15	due	due	ADP
bracis-28373	26	16	to	to	ADP
bracis-28373	26	17	their	their	PRON
bracis-28373	26	18	ability	ability	NOUN
bracis-28373	26	19	to	to	PART
bracis-28373	26	20	learn	learn	VERB
bracis-28373	26	21	and	and	CCONJ
bracis-28373	26	22	generalize	generalize	VERB
bracis-28373	26	23	complex	complex	ADJ
bracis-28373	26	24	patterns	pattern	NOUN
bracis-28373	26	25	in	in	ADP
bracis-28373	26	26	large	large	ADJ
bracis-28373	26	27	datasets	dataset	NOUN
bracis-28373	26	28	.	.	PUNCT
bracis-28373	27	1	however	however	ADV
bracis-28373	27	2	,	,	PUNCT
bracis-28373	27	3	despite	despite	SCONJ
bracis-28373	27	4	their	their	PRON
bracis-28373	27	5	promising	promising	ADJ
bracis-28373	27	6	results	result	NOUN
bracis-28373	27	7	,	,	PUNCT
bracis-28373	27	8	neural	neural	ADJ
bracis-28373	27	9	networks	network	NOUN
bracis-28373	27	10	have	have	VERB
bracis-28373	27	11	limitations	limitation	NOUN
bracis-28373	27	12	that	that	PRON
bracis-28373	27	13	can	can	AUX
bracis-28373	27	14	restrict	restrict	VERB
bracis-28373	27	15	their	their	PRON
bracis-28373	27	16	applications	application	NOUN
bracis-28373	27	17	,	,	PUNCT
bracis-28373	27	18	such	such	ADJ
bracis-28373	27	19	as	as	ADP
bracis-28373	27	20	difficulty	difficulty	NOUN
bracis-28373	27	21	in	in	ADP
bracis-28373	27	22	model	model	NOUN
bracis-28373	27	23	calibration	calibration	NOUN
bracis-28373	27	24	and	and	CCONJ
bracis-28373	27	25	overconfidence	overconfidence	NOUN
bracis-28373	27	26	in	in	ADP
bracis-28373	27	27	predictions	prediction	NOUN
bracis-28373	27	28	,	,	PUNCT
bracis-28373	27	29	especially	especially	ADV
bracis-28373	27	30	when	when	SCONJ
bracis-28373	27	31	the	the	DET
bracis-28373	27	32	data	data	NOUN
bracis-28373	27	33	distribution	distribution	NOUN
bracis-28373	27	34	changes	change	NOUN
bracis-28373	27	35	between	between	ADP
bracis-28373	27	36	training	training	NOUN
bracis-28373	27	37	and	and	CCONJ
bracis-28373	27	38	testing	testing	NOUN
bracis-28373	27	39	 	 	SPACE
bracis-28373	28	1	[	[	X
bracis-28373	28	2	10	10	NUM
bracis-28373	28	3	]	]	PUNCT
bracis-28373	28	4	.	.	PUNCT
bracis-28373	29	1	this	this	DET
bracis-28373	29	2	overconfidence	overconfidence	NOUN
bracis-28373	29	3	problem	problem	NOUN
bracis-28373	29	4	is	be	AUX
bracis-28373	29	5	where	where	SCONJ
bracis-28373	29	6	neural	neural	ADJ
bracis-28373	29	7	networks	network	NOUN
bracis-28373	29	8	exhibit	exhibit	VERB
bracis-28373	29	9	excessively	excessively	ADV
bracis-28373	29	10	high	high	ADJ
bracis-28373	29	11	confidence	confidence	NOUN
bracis-28373	29	12	levels	level	NOUN
bracis-28373	29	13	in	in	ADP
bracis-28373	29	14	their	their	PRON
bracis-28373	29	15	predictions	prediction	NOUN
bracis-28373	29	16	,	,	PUNCT
bracis-28373	29	17	even	even	ADV
bracis-28373	29	18	when	when	SCONJ
bracis-28373	29	19	these	these	DET
bracis-28373	29	20	predictions	prediction	NOUN
bracis-28373	29	21	are	be	AUX
bracis-28373	29	22	incorrect	incorrect	ADJ
bracis-28373	29	23	.	.	PUNCT
bracis-28373	30	1	this	this	PRON
bracis-28373	30	2	happens	happen	VERB
bracis-28373	30	3	because	because	SCONJ
bracis-28373	30	4	neural	neural	ADJ
bracis-28373	30	5	networks	network	NOUN
bracis-28373	30	6	are	be	AUX
bracis-28373	30	7	trained	train	VERB
bracis-28373	30	8	to	to	PART
bracis-28373	30	9	maximize	maximize	VERB
bracis-28373	30	10	the	the	DET
bracis-28373	30	11	accuracy	accuracy	NOUN
bracis-28373	30	12	of	of	ADP
bracis-28373	30	13	their	their	PRON
bracis-28373	30	14	predictions	prediction	NOUN
bracis-28373	30	15	without	without	ADP
bracis-28373	30	16	considering	consider	VERB
bracis-28373	30	17	the	the	DET
bracis-28373	30	18	uncertainty	uncertainty	NOUN
bracis-28373	30	19	associated	associate	VERB
bracis-28373	30	20	with	with	ADP
bracis-28373	30	21	the	the	DET
bracis-28373	30	22	input	input	NOUN
bracis-28373	30	23	data	datum	NOUN
bracis-28373	30	24	.	.	PUNCT
bracis-28373	31	1	as	as	ADP
bracis-28373	31	2	a	a	DET
bracis-28373	31	3	result	result	NOUN
bracis-28373	31	4	,	,	PUNCT
bracis-28373	31	5	neural	neural	ADJ
bracis-28373	31	6	networks	network	NOUN
bracis-28373	31	7	may	may	AUX
bracis-28373	31	8	exhibit	exhibit	VERB
bracis-28373	31	9	overconfidence	overconfidence	NOUN
bracis-28373	31	10	in	in	ADP
bracis-28373	31	11	their	their	PRON
bracis-28373	31	12	predictions	prediction	NOUN
bracis-28373	31	13	,	,	PUNCT
bracis-28373	31	14	even	even	ADV
bracis-28373	31	15	when	when	SCONJ
bracis-28373	31	16	the	the	DET
bracis-28373	31	17	input	input	NOUN
bracis-28373	31	18	data	data	NOUN
bracis-28373	31	19	is	be	AUX
bracis-28373	31	20	ambiguous	ambiguous	ADJ
bracis-28373	31	21	or	or	CCONJ
bracis-28373	31	22	noisy	noisy	ADJ
bracis-28373	31	23	.	.	PUNCT
bracis-28373	32	1	bayesian	bayesian	NOUN
bracis-28373	32	2	neural	neural	ADJ
bracis-28373	32	3	networks	network	NOUN
bracis-28373	32	4	(	(	PUNCT
bracis-28373	32	5	bnns	bnns	ADJ
bracis-28373	32	6	)	)	PUNCT
bracis-28373	32	7	are	be	AUX
bracis-28373	32	8	models	model	NOUN
bracis-28373	32	9	capable	capable	ADJ
bracis-28373	32	10	of	of	ADP
bracis-28373	32	11	quantifying	quantify	VERB
bracis-28373	32	12	uncertainty	uncertainty	NOUN
bracis-28373	32	13	and	and	CCONJ
bracis-28373	32	14	using	use	VERB
bracis-28373	32	15	it	it	PRON
bracis-28373	32	16	to	to	PART
bracis-28373	32	17	develop	develop	VERB
bracis-28373	32	18	more	more	ADV
bracis-28373	32	19	accurate	accurate	ADJ
bracis-28373	32	20	learning	learn	VERB
bracis-28373	32	21	algorithms	algorithm	NOUN
bracis-28373	32	22	 	 	SPACE
bracis-28373	33	1	[	[	X
bracis-28373	33	2	9	9	NUM
bracis-28373	33	3	]	]	PUNCT
bracis-28373	33	4	.	.	PUNCT
bracis-28373	34	1	in	in	ADP
bracis-28373	34	2	addition	addition	NOUN
bracis-28373	34	3	,	,	PUNCT
bracis-28373	34	4	bnns	bnn	NOUN
bracis-28373	34	5	tend	tend	VERB
bracis-28373	34	6	to	to	PART
bracis-28373	34	7	mitigate	mitigate	VERB
bracis-28373	34	8	the	the	DET
bracis-28373	34	9	problem	problem	NOUN
bracis-28373	34	10	of	of	ADP
bracis-28373	34	11	neural	neural	ADJ
bracis-28373	34	12	networks	network	NOUN
bracis-28373	34	13	’	'	PUNCT
bracis-28373	34	14	overconfidence	overconfidence	NOUN
bracis-28373	34	15	 	 	SPACE
bracis-28373	35	1	[	[	X
bracis-28373	35	2	8	8	NUM
bracis-28373	35	3	]	]	PUNCT
bracis-28373	35	4	.	.	PUNCT
bracis-28373	36	1	this	this	DET
bracis-28373	36	2	approach	approach	NOUN
bracis-28373	36	3	allows	allow	VERB
bracis-28373	36	4	neural	neural	ADJ
bracis-28373	36	5	networks	network	NOUN
bracis-28373	36	6	to	to	PART
bracis-28373	36	7	produce	produce	VERB
bracis-28373	36	8	a	a	DET
bracis-28373	36	9	probability	probability	NOUN
bracis-28373	36	10	distribution	distribution	NOUN
bracis-28373	36	11	for	for	ADP
bracis-28373	36	12	the	the	DET
bracis-28373	36	13	output	output	NOUN
bracis-28373	36	14	rather	rather	ADV
bracis-28373	36	15	than	than	ADP
bracis-28373	36	16	just	just	ADV
bracis-28373	36	17	a	a	DET
bracis-28373	36	18	single	single	ADJ
bracis-28373	36	19	output	output	NOUN
bracis-28373	36	20	,	,	PUNCT
bracis-28373	36	21	considering	consider	VERB
bracis-28373	36	22	the	the	DET
bracis-28373	36	23	uncertainty	uncertainty	NOUN
bracis-28373	36	24	associated	associate	VERB
bracis-28373	36	25	with	with	ADP
bracis-28373	36	26	the	the	DET
bracis-28373	36	27	input	input	NOUN
bracis-28373	36	28	data	datum	NOUN
bracis-28373	36	29	.	.	PUNCT
bracis-28373	37	1	this	this	PRON
bracis-28373	37	2	allows	allow	VERB
bracis-28373	37	3	the	the	DET
bracis-28373	37	4	network	network	NOUN
bracis-28373	37	5	to	to	PART
bracis-28373	37	6	assess	assess	VERB
bracis-28373	37	7	its	its	PRON
bracis-28373	37	8	confidence	confidence	NOUN
bracis-28373	37	9	in	in	ADP
bracis-28373	37	10	the	the	DET
bracis-28373	37	11	prediction	prediction	NOUN
bracis-28373	37	12	and	and	CCONJ
bracis-28373	37	13	make	make	VERB
bracis-28373	37	14	more	more	ADV
bracis-28373	37	15	informed	informed	ADJ
bracis-28373	37	16	decisions	decision	NOUN
bracis-28373	37	17	,	,	PUNCT
bracis-28373	37	18	improving	improve	VERB
bracis-28373	37	19	its	its	PRON
bracis-28373	37	20	generalization	generalization	NOUN
bracis-28373	37	21	and	and	CCONJ
bracis-28373	37	22	making	make	VERB
bracis-28373	37	23	it	it	PRON
bracis-28373	37	24	more	more	ADV
bracis-28373	37	25	robust	robust	ADJ
bracis-28373	37	26	and	and	CCONJ
bracis-28373	37	27	reliable	reliable	ADJ
bracis-28373	37	28	.	.	PUNCT
bracis-28373	38	1	although	although	SCONJ
bracis-28373	38	2	implementing	implement	VERB
bracis-28373	38	3	bayesian	bayesian	NOUN
bracis-28373	38	4	neural	neural	ADJ
bracis-28373	38	5	networks	network	NOUN
bracis-28373	38	6	may	may	AUX
bracis-28373	38	7	be	be	AUX
bracis-28373	38	8	more	more	ADV
bracis-28373	38	9	complex	complex	ADJ
bracis-28373	38	10	,	,	PUNCT
bracis-28373	38	11	the	the	DET
bracis-28373	38	12	advantages	advantage	NOUN
bracis-28373	38	13	in	in	ADP
bracis-28373	38	14	terms	term	NOUN
bracis-28373	38	15	of	of	ADP
bracis-28373	38	16	accuracy	accuracy	NOUN
bracis-28373	38	17	and	and	CCONJ
bracis-28373	38	18	confidence	confidence	NOUN
bracis-28373	38	19	in	in	ADP
bracis-28373	38	20	their	their	PRON
bracis-28373	38	21	predictions	prediction	NOUN
bracis-28373	38	22	are	be	AUX
bracis-28373	38	23	significant	significant	ADJ
bracis-28373	38	24	 	 	SPACE
bracis-28373	39	1	[	[	X
bracis-28373	39	2	11	11	NUM
bracis-28373	39	3	]	]	PUNCT
bracis-28373	39	4	.	.	PUNCT
bracis-28373	40	1	for	for	ADP
bracis-28373	40	2	example	example	NOUN
bracis-28373	40	3	,	,	PUNCT
bracis-28373	40	4	we	we	PRON
bracis-28373	40	5	can	can	AUX
bracis-28373	40	6	see	see	VERB
bracis-28373	40	7	an	an	DET
bracis-28373	40	8	illustration	illustration	NOUN
bracis-28373	40	9	in	in	ADP
bracis-28373	40	10	fig	fig	NOUN
bracis-28373	40	11	.	.	PUNCT
bracis-28373	40	12	 	 	SPACE
bracis-28373	41	1	1	1	NUM
bracis-28373	41	2	,	,	PUNCT
bracis-28373	41	3	an	an	DET
bracis-28373	41	4	example	example	NOUN
bracis-28373	41	5	of	of	ADP
bracis-28373	41	6	the	the	DET
bracis-28373	41	7	decision	decision	NOUN
bracis-28373	41	8	region	region	NOUN
bracis-28373	41	9	of	of	ADP
bracis-28373	41	10	neural	neural	ADJ
bracis-28373	41	11	networks	network	NOUN
bracis-28373	41	12	(	(	PUNCT
bracis-28373	41	13	bayesian	bayesian	NOUN
bracis-28373	41	14	)	)	PUNCT
bracis-28373	41	15	.	.	PUNCT
bracis-28373	42	1	in	in	ADP
bracis-28373	42	2	this	this	DET
bracis-28373	42	3	example	example	NOUN
bracis-28373	42	4	,	,	PUNCT
bracis-28373	42	5	we	we	PRON
bracis-28373	42	6	observe	observe	VERB
bracis-28373	42	7	that	that	SCONJ
bracis-28373	42	8	bnns	bnns	PROPN
bracis-28373	42	9	present	present	ADJ
bracis-28373	42	10	smoother	smooth	ADJ
bracis-28373	42	11	decision	decision	NOUN
bracis-28373	42	12	regions	region	NOUN
bracis-28373	42	13	,	,	PUNCT
bracis-28373	42	14	which	which	PRON
bracis-28373	42	15	implies	imply	VERB
bracis-28373	42	16	more	more	ADV
bracis-28373	42	17	realistic	realistic	ADJ
bracis-28373	42	18	confidence	confidence	NOUN
bracis-28373	42	19	about	about	ADP
bracis-28373	42	20	predictions	prediction	NOUN
bracis-28373	42	21	.	.	PUNCT
bracis-28373	43	1	furthermore	furthermore	ADV
bracis-28373	43	2	,	,	PUNCT
bracis-28373	43	3	neural	neural	ADJ
bracis-28373	43	4	networks	network	NOUN
bracis-28373	43	5	are	be	AUX
bracis-28373	43	6	typically	typically	ADV
bracis-28373	43	7	confident	confident	ADJ
bracis-28373	43	8	even	even	ADV
bracis-28373	43	9	in	in	ADP
bracis-28373	43	10	regions	region	NOUN
bracis-28373	43	11	where	where	SCONJ
bracis-28373	43	12	the	the	DET
bracis-28373	43	13	uncertainty	uncertainty	NOUN
bracis-28373	43	14	is	be	AUX
bracis-28373	43	15	high	high	ADJ
bracis-28373	43	16	,	,	PUNCT
bracis-28373	43	17	such	such	ADJ
bracis-28373	43	18	as	as	ADP
bracis-28373	43	19	on	on	ADP
bracis-28373	43	20	the	the	DET
bracis-28373	43	21	borders	border	NOUN
bracis-28373	43	22	of	of	ADP
bracis-28373	43	23	regions	region	NOUN
bracis-28373	43	24	.	.	PUNCT
bracis-28373	44	1	fig	fig	NOUN
bracis-28373	44	2	.	.	PUNCT
bracis-28373	45	1	1	1	X
bracis-28373	45	2	.	.	X
bracis-28373	45	3	illustration	illustration	NOUN
bracis-28373	45	4	of	of	ADP
bracis-28373	45	5	decision	decision	NOUN
bracis-28373	45	6	region	region	NOUN
bracis-28373	45	7	of	of	ADP
bracis-28373	45	8	(	(	PUNCT
bracis-28373	45	9	bayesian	bayesian	NOUN
bracis-28373	45	10	)	)	PUNCT
bracis-28373	45	11	neural	neural	ADJ
bracis-28373	45	12	network	network	NOUN
bracis-28373	45	13	.	.	PUNCT
bracis-28373	46	1	the	the	DET
bracis-28373	46	2	dataset	dataset	NOUN
bracis-28373	46	3	used	use	VERB
bracis-28373	46	4	in	in	ADP
bracis-28373	46	5	this	this	DET
bracis-28373	46	6	experiment	experiment	NOUN
bracis-28373	46	7	is	be	AUX
bracis-28373	46	8	synthetic	synthetic	ADJ
bracis-28373	46	9	and	and	CCONJ
bracis-28373	46	10	consists	consist	VERB
bracis-28373	46	11	of	of	ADP
bracis-28373	46	12	200	200	NUM
bracis-28373	46	13	samples	sample	NOUN
bracis-28373	46	14	.	.	PUNCT
bracis-28373	47	1	each	each	DET
bracis-28373	47	2	sample	sample	NOUN
bracis-28373	47	3	has	have	VERB
bracis-28373	47	4	two	two	NUM
bracis-28373	47	5	features	feature	NOUN
bracis-28373	47	6	(	(	PUNCT
bracis-28373	47	7	2d	2d	NUM
bracis-28373	47	8	dimension	dimension	NOUN
bracis-28373	47	9	)	)	PUNCT
bracis-28373	47	10	randomly	randomly	ADV
bracis-28373	47	11	generated	generate	VERB
bracis-28373	47	12	from	from	ADP
bracis-28373	47	13	a	a	DET
bracis-28373	47	14	normal	normal	ADJ
bracis-28373	47	15	distribution	distribution	NOUN
bracis-28373	47	16	.	.	PUNCT
bracis-28373	48	1	the	the	DET
bracis-28373	48	2	output	output	NOUN
bracis-28373	48	3	variable	variable	NOUN
bracis-28373	48	4	is	be	AUX
bracis-28373	48	5	determined	determine	VERB
bracis-28373	48	6	by	by	ADP
bracis-28373	48	7	applying	apply	VERB
bracis-28373	48	8	the	the	DET
bracis-28373	48	9	xor	xor	PROPN
bracis-28373	48	10	logical	logical	ADJ
bracis-28373	48	11	operation	operation	NOUN
bracis-28373	48	12	to	to	ADP
bracis-28373	48	13	the	the	DET
bracis-28373	48	14	two	two	NUM
bracis-28373	48	15	input	input	NOUN
bracis-28373	48	16	features	feature	NOUN
bracis-28373	48	17	.	.	PUNCT
bracis-28373	49	1	the	the	DET
bracis-28373	49	2	goal	goal	NOUN
bracis-28373	49	3	is	be	AUX
bracis-28373	49	4	to	to	PART
bracis-28373	49	5	train	train	VERB
bracis-28373	49	6	a	a	DET
bracis-28373	49	7	(	(	PUNCT
bracis-28373	49	8	bayesian	bayesian	NOUN
bracis-28373	49	9	)	)	PUNCT
bracis-28373	49	10	neural	neural	ADJ
bracis-28373	49	11	network	network	NOUN
bracis-28373	49	12	model	model	NOUN
bracis-28373	49	13	to	to	PART
bracis-28373	49	14	make	make	VERB
bracis-28373	49	15	accurate	accurate	ADJ
bracis-28373	49	16	predictions	prediction	NOUN
bracis-28373	49	17	.	.	PUNCT
bracis-28373	50	1	full	full	ADJ
bracis-28373	50	2	size	size	NOUN
bracis-28373	50	3	image	image	NOUN
bracis-28373	50	4	this	this	DET
bracis-28373	50	5	work	work	NOUN
bracis-28373	50	6	proposes	propose	VERB
bracis-28373	50	7	a	a	DET
bracis-28373	50	8	novel	novel	ADJ
bracis-28373	50	9	attack	attack	NOUN
bracis-28373	50	10	approach	approach	NOUN
bracis-28373	50	11	to	to	ADP
bracis-28373	50	12	poisoning	poisoning	NOUN
bracis-28373	50	13	labels	label	NOUN
bracis-28373	50	14	using	use	VERB
bracis-28373	50	15	bayesian	bayesian	NOUN
bracis-28373	50	16	neural	neural	ADJ
bracis-28373	50	17	networks	network	NOUN
bracis-28373	50	18	in	in	ADP
bracis-28373	50	19	federated	federated	ADJ
bracis-28373	50	20	environments	environment	NOUN
bracis-28373	50	21	.	.	PUNCT
bracis-28373	51	1	label	label	NOUN
bracis-28373	51	2	poisoning	poisoning	NOUN
bracis-28373	51	3	attacks	attack	NOUN
bracis-28373	51	4	change	change	VERB
bracis-28373	51	5	training	training	NOUN
bracis-28373	51	6	data	datum	NOUN
bracis-28373	51	7	labels	label	NOUN
bracis-28373	51	8	,	,	PUNCT
bracis-28373	51	9	deviating	deviate	VERB
bracis-28373	51	10	the	the	DET
bracis-28373	51	11	model	model	NOUN
bracis-28373	51	12	from	from	ADP
bracis-28373	51	13	its	its	PRON
bracis-28373	51	14	original	original	ADJ
bracis-28373	51	15	goal	goal	NOUN
bracis-28373	51	16	.	.	PUNCT
bracis-28373	52	1	as	as	SCONJ
bracis-28373	52	2	bnns	bnn	NOUN
bracis-28373	52	3	incorporate	incorporate	VERB
bracis-28373	52	4	the	the	DET
bracis-28373	52	5	principle	principle	NOUN
bracis-28373	52	6	of	of	ADP
bracis-28373	52	7	parsimony	parsimony	NOUN
bracis-28373	52	8	(	(	PUNCT
bracis-28373	52	9	occam	occam	PROPN
bracis-28373	52	10	’s	’s	PART
bracis-28373	52	11	razor	razor	NOUN
bracis-28373	52	12	)	)	PUNCT
bracis-28373	52	13	,	,	PUNCT
bracis-28373	52	14	we	we	PRON
bracis-28373	52	15	hypothesize	hypothesize	VERB
bracis-28373	52	16	that	that	SCONJ
bracis-28373	52	17	a	a	DET
bracis-28373	52	18	label	label	NOUN
bracis-28373	52	19	poisoning	poisoning	NOUN
bracis-28373	52	20	attack	attack	NOUN
bracis-28373	52	21	model	model	NOUN
bracis-28373	52	22	trained	train	VERB
bracis-28373	52	23	using	use	VERB
bracis-28373	52	24	the	the	DET
bracis-28373	52	25	uncertainty	uncertainty	NOUN
bracis-28373	52	26	quantification	quantification	NOUN
bracis-28373	52	27	provided	provide	VERB
bracis-28373	52	28	by	by	ADP
bracis-28373	52	29	bnns	bnn	NOUN
bracis-28373	52	30	can	can	AUX
bracis-28373	52	31	maximize	maximize	VERB
bracis-28373	52	32	the	the	DET
bracis-28373	52	33	adherence	adherence	NOUN
bracis-28373	52	34	of	of	ADP
bracis-28373	52	35	malicious	malicious	ADJ
bracis-28373	52	36	data	datum	NOUN
bracis-28373	52	37	to	to	ADP
bracis-28373	52	38	the	the	DET
bracis-28373	52	39	model	model	NOUN
bracis-28373	52	40	while	while	SCONJ
bracis-28373	52	41	also	also	ADV
bracis-28373	52	42	estimating	estimate	VERB
bracis-28373	52	43	a	a	DET
bracis-28373	52	44	poisoned	poison	VERB
bracis-28373	52	45	model	model	NOUN
bracis-28373	52	46	with	with	ADP
bracis-28373	52	47	lower	low	ADJ
bracis-28373	52	48	complexity	complexity	NOUN
bracis-28373	52	49	,	,	PUNCT
bracis-28373	52	50	making	make	VERB
bracis-28373	52	51	it	it	PRON
bracis-28373	52	52	difficult	difficult	ADJ
bracis-28373	52	53	to	to	PART
bracis-28373	52	54	detect	detect	VERB
bracis-28373	52	55	attacks	attack	NOUN
bracis-28373	52	56	in	in	ADP
bracis-28373	52	57	federated	federated	ADJ
bracis-28373	52	58	environments	environment	NOUN
bracis-28373	52	59	.	.	PUNCT
bracis-28373	53	1	this	this	DET
bracis-28373	53	2	work	work	NOUN
bracis-28373	53	3	aims	aim	VERB
bracis-28373	53	4	to	to	PART
bracis-28373	53	5	propose	propose	VERB
bracis-28373	53	6	and	and	CCONJ
bracis-28373	53	7	evaluate	evaluate	VERB
bracis-28373	53	8	this	this	DET
bracis-28373	53	9	approach	approach	NOUN
bracis-28373	53	10	,	,	PUNCT
bracis-28373	53	11	presenting	present	VERB
bracis-28373	53	12	experimental	experimental	ADJ
bracis-28373	53	13	results	result	NOUN
bracis-28373	53	14	that	that	PRON
bracis-28373	53	15	demonstrate	demonstrate	VERB
bracis-28373	53	16	its	its	PRON
bracis-28373	53	17	effectiveness	effectiveness	NOUN
bracis-28373	53	18	in	in	ADP
bracis-28373	53	19	generating	generate	VERB
bracis-28373	53	20	poisoned	poison	VERB
bracis-28373	53	21	models	model	NOUN
bracis-28373	53	22	in	in	ADP
bracis-28373	53	23	federated	federated	ADJ
bracis-28373	53	24	environments	environment	NOUN
bracis-28373	53	25	.	.	PUNCT
bracis-28373	54	1	we	we	PRON
bracis-28373	54	2	organized	organize	VERB
bracis-28373	54	3	this	this	DET
bracis-28373	54	4	paper	paper	NOUN
bracis-28373	54	5	as	as	SCONJ
bracis-28373	54	6	follows	follow	VERB
bracis-28373	54	7	:	:	PUNCT
bracis-28373	54	8	sect	sect	NOUN
bracis-28373	54	9	.	.	PUNCT
bracis-28373	54	10	 	 	SPACE
bracis-28373	55	1	2	2	NUM
bracis-28373	55	2	presents	present	VERB
bracis-28373	55	3	the	the	DET
bracis-28373	55	4	related	relate	VERB
bracis-28373	55	5	works	work	NOUN
bracis-28373	55	6	to	to	ADP
bracis-28373	55	7	security	security	NOUN
bracis-28373	55	8	in	in	ADP
bracis-28373	55	9	fl	fl	NUM
bracis-28373	55	10	environments	environment	NOUN
bracis-28373	55	11	;	;	PUNCT
bracis-28373	55	12	sect	sect	NOUN
bracis-28373	55	13	.	.	PUNCT
bracis-28373	55	14	 	 	SPACE
bracis-28373	56	1	3	3	NUM
bracis-28373	56	2	describes	describe	VERB
bracis-28373	56	3	our	our	PRON
bracis-28373	56	4	proposal	proposal	NOUN
bracis-28373	56	5	and	and	CCONJ
bracis-28373	56	6	some	some	DET
bracis-28373	56	7	notations	notation	NOUN
bracis-28373	56	8	review	review	VERB
bracis-28373	56	9	for	for	ADP
bracis-28373	56	10	a	a	DET
bracis-28373	56	11	good	good	ADJ
bracis-28373	56	12	understanding	understanding	NOUN
bracis-28373	56	13	of	of	ADP
bracis-28373	56	14	our	our	PRON
bracis-28373	56	15	proposal	proposal	NOUN
bracis-28373	56	16	;	;	PUNCT
bracis-28373	56	17	sect	sect	NOUN
bracis-28373	56	18	.	.	PUNCT
bracis-28373	56	19	 	 	SPACE
bracis-28373	57	1	4	4	NUM
bracis-28373	57	2	describes	describe	VERB
bracis-28373	57	3	the	the	DET
bracis-28373	57	4	experimental	experimental	ADJ
bracis-28373	57	5	setup	setup	NOUN
bracis-28373	57	6	used	use	VERB
bracis-28373	57	7	to	to	PART
bracis-28373	57	8	analyze	analyze	VERB
bracis-28373	57	9	the	the	DET
bracis-28373	57	10	data	datum	NOUN
bracis-28373	57	11	;	;	PUNCT
bracis-28373	57	12	sect	sect	NOUN
bracis-28373	57	13	.	.	PUNCT
bracis-28373	57	14	 	 	SPACE
bracis-28373	58	1	5	5	NUM
bracis-28373	58	2	presents	present	VERB
bracis-28373	58	3	the	the	DET
bracis-28373	58	4	main	main	ADJ
bracis-28373	58	5	results	result	NOUN
bracis-28373	58	6	and	and	CCONJ
bracis-28373	58	7	discussions	discussion	NOUN
bracis-28373	58	8	;	;	PUNCT
bracis-28373	58	9	and	and	CCONJ
bracis-28373	58	10	sect	sect	NOUN
bracis-28373	58	11	.	.	PUNCT
bracis-28373	58	12	 	 	SPACE
bracis-28373	58	13	6	6	NUM
bracis-28373	58	14	concludes	conclude	VERB
bracis-28373	58	15	this	this	DET
bracis-28373	58	16	work	work	NOUN
bracis-28373	58	17	.	.	PUNCT
bracis-28373	59	1	2	2	NUM
bracis-28373	59	2	related	related	ADJ
bracis-28373	59	3	work	work	NOUN
bracis-28373	59	4	the	the	DET
bracis-28373	59	5	security	security	NOUN
bracis-28373	59	6	issues	issue	NOUN
bracis-28373	59	7	in	in	ADP
bracis-28373	59	8	machine	machine	NOUN
bracis-28373	59	9	learning	learn	VERB
bracis-28373	59	10	systems	system	NOUN
bracis-28373	59	11	,	,	PUNCT
bracis-28373	59	12	and	and	CCONJ
bracis-28373	59	13	consequently	consequently	ADV
bracis-28373	59	14	federated	federated	ADJ
bracis-28373	59	15	learning	learning	NOUN
bracis-28373	59	16	,	,	PUNCT
bracis-28373	59	17	have	have	AUX
bracis-28373	59	18	been	be	AUX
bracis-28373	59	19	extensively	extensively	ADV
bracis-28373	59	20	studied	study	VERB
bracis-28373	59	21	 	 	SPACE
bracis-28373	60	1	[	[	X
bracis-28373	60	2	17	17	NUM
bracis-28373	60	3	,	,	PUNCT
bracis-28373	60	4	21	21	NUM
bracis-28373	60	5	,	,	PUNCT
bracis-28373	60	6	27	27	NUM
bracis-28373	60	7	]	]	PUNCT
bracis-28373	60	8	.	.	PUNCT
bracis-28373	61	1	in	in	ADP
bracis-28373	61	2	traditional	traditional	ADJ
bracis-28373	61	3	machine	machine	NOUN
bracis-28373	61	4	learning	learning	NOUN
bracis-28373	61	5	,	,	PUNCT
bracis-28373	61	6	the	the	DET
bracis-28373	61	7	learning	learning	NOUN
bracis-28373	61	8	phase	phase	NOUN
bracis-28373	61	9	is	be	AUX
bracis-28373	61	10	typically	typically	ADV
bracis-28373	61	11	protected	protect	VERB
bracis-28373	61	12	and	and	CCONJ
bracis-28373	61	13	centralized	centralize	VERB
bracis-28373	61	14	in	in	ADP
bracis-28373	61	15	a	a	DET
bracis-28373	61	16	unique	unique	ADJ
bracis-28373	61	17	system	system	NOUN
bracis-28373	61	18	 	 	SPACE
bracis-28373	62	1	[	[	X
bracis-28373	62	2	13	13	NUM
bracis-28373	62	3	]	]	PUNCT
bracis-28373	62	4	.	.	PUNCT
bracis-28373	63	1	specifically	specifically	ADV
bracis-28373	63	2	,	,	PUNCT
bracis-28373	63	3	the	the	DET
bracis-28373	63	4	approaches	approach	NOUN
bracis-28373	63	5	in	in	ADP
bracis-28373	63	6	literature	literature	NOUN
bracis-28373	63	7	usually	usually	ADV
bracis-28373	63	8	consider	consider	VERB
bracis-28373	63	9	that	that	SCONJ
bracis-28373	63	10	malicious	malicious	ADJ
bracis-28373	63	11	clients	client	NOUN
bracis-28373	63	12	act	act	VERB
bracis-28373	63	13	during	during	ADP
bracis-28373	63	14	inference	inference	NOUN
bracis-28373	63	15	,	,	PUNCT
bracis-28373	63	16	i.e.	i.e.	X
bracis-28373	63	17	,	,	PUNCT
bracis-28373	63	18	the	the	DET
bracis-28373	63	19	attacked	attack	VERB
bracis-28373	63	20	model	model	NOUN
bracis-28373	63	21	is	be	AUX
bracis-28373	63	22	already	already	ADV
bracis-28373	63	23	in	in	ADP
bracis-28373	63	24	production	production	NOUN
bracis-28373	63	25	 	 	SPACE
bracis-28373	64	1	[	[	X
bracis-28373	64	2	12	12	NUM
bracis-28373	64	3	]	]	PUNCT
bracis-28373	64	4	.	.	PUNCT
bracis-28373	65	1	in	in	ADP
bracis-28373	65	2	fl	fl	PROPN
bracis-28373	65	3	,	,	PUNCT
bracis-28373	65	4	malicious	malicious	ADJ
bracis-28373	65	5	clients	client	NOUN
bracis-28373	65	6	usually	usually	ADV
bracis-28373	65	7	exploit	exploit	VERB
bracis-28373	65	8	the	the	DET
bracis-28373	65	9	vulnerability	vulnerability	NOUN
bracis-28373	65	10	of	of	ADP
bracis-28373	65	11	the	the	DET
bracis-28373	65	12	models	model	NOUN
bracis-28373	65	13	during	during	ADP
bracis-28373	65	14	the	the	DET
bracis-28373	65	15	learning	learning	NOUN
bracis-28373	65	16	phase	phase	NOUN
bracis-28373	65	17	 	 	SPACE
bracis-28373	66	1	[	[	X
bracis-28373	66	2	3	3	NUM
bracis-28373	66	3	]	]	PUNCT
bracis-28373	66	4	.	.	PUNCT
bracis-28373	67	1	in	in	ADP
bracis-28373	67	2	general	general	ADJ
bracis-28373	67	3	,	,	PUNCT
bracis-28373	67	4	malicious	malicious	ADJ
bracis-28373	67	5	clients	client	NOUN
bracis-28373	67	6	attacking	attack	VERB
bracis-28373	67	7	an	an	DET
bracis-28373	67	8	fl	fl	NOUN
bracis-28373	67	9	model	model	NOUN
bracis-28373	67	10	have	have	VERB
bracis-28373	67	11	one	one	NUM
bracis-28373	67	12	of	of	ADP
bracis-28373	67	13	two	two	NUM
bracis-28373	67	14	adversarial	adversarial	ADJ
bracis-28373	67	15	goals	goal	NOUN
bracis-28373	67	16	:	:	PUNCT
bracis-28373	67	17	case	case	NOUN
bracis-28373	67	18	i.	i.	NOUN
bracis-28373	67	19	reconstruct	reconstruct	VERB
bracis-28373	67	20	or	or	CCONJ
bracis-28373	67	21	learn	learn	VERB
bracis-28373	67	22	client	client	NOUN
bracis-28373	67	23	/	/	SYM
bracis-28373	67	24	model	model	NOUN
bracis-28373	67	25	information	information	NOUN
bracis-28373	67	26	based	base	VERB
bracis-28373	67	27	on	on	ADP
bracis-28373	67	28	data	datum	NOUN
bracis-28373	67	29	transmitted	transmit	VERB
bracis-28373	67	30	in	in	ADP
bracis-28373	67	31	the	the	DET
bracis-28373	67	32	federated	federated	ADJ
bracis-28373	67	33	training	training	NOUN
bracis-28373	67	34	process	process	NOUN
bracis-28373	67	35	,	,	PUNCT
bracis-28373	67	36	and	and	CCONJ
bracis-28373	67	37	case	case	NOUN
bracis-28373	67	38	ii	ii	PROPN
bracis-28373	67	39	.	.	PUNCT
bracis-28373	67	40	force	force	VERB
bracis-28373	67	41	the	the	DET
bracis-28373	67	42	model	model	NOUN
bracis-28373	67	43	to	to	PART
bracis-28373	67	44	behave	behave	VERB
bracis-28373	67	45	differently	differently	ADV
bracis-28373	67	46	than	than	ADP
bracis-28373	67	47	intended	intended	ADJ
bracis-28373	67	48	,	,	PUNCT
bracis-28373	67	49	invalidate	invalidate	VERB
bracis-28373	67	50	or	or	CCONJ
bracis-28373	67	51	train	train	VERB
bracis-28373	67	52	it	it	PRON
bracis-28373	67	53	for	for	ADP
bracis-28373	67	54	a	a	DET
bracis-28373	67	55	specific	specific	ADJ
bracis-28373	67	56	purpose	purpose	NOUN
bracis-28373	67	57	(	(	PUNCT
bracis-28373	67	58	e.g.	e.g.	ADV
bracis-28373	67	59	,	,	PUNCT
bracis-28373	67	60	poisoning	poisoning	NOUN
bracis-28373	67	61	attack	attack	NOUN
bracis-28373	67	62	)	)	PUNCT
bracis-28373	67	63	.	.	PUNCT
bracis-28373	68	1	in	in	ADP
bracis-28373	68	2	this	this	DET
bracis-28373	68	3	proposal	proposal	NOUN
bracis-28373	68	4	,	,	PUNCT
bracis-28373	68	5	we	we	PRON
bracis-28373	68	6	focus	focus	VERB
bracis-28373	68	7	on	on	ADP
bracis-28373	68	8	the	the	DET
bracis-28373	68	9	problems	problem	NOUN
bracis-28373	68	10	related	relate	VERB
bracis-28373	68	11	to	to	ADP
bracis-28373	68	12	attacks	attack	NOUN
bracis-28373	68	13	that	that	PRON
bracis-28373	68	14	aim	aim	VERB
bracis-28373	68	15	to	to	PART
bracis-28373	68	16	degrade	degrade	VERB
bracis-28373	68	17	the	the	DET
bracis-28373	68	18	performance	performance	NOUN
bracis-28373	68	19	of	of	ADP
bracis-28373	68	20	the	the	DET
bracis-28373	68	21	aggregated	aggregate	VERB
bracis-28373	68	22	model	model	NOUN
bracis-28373	68	23	(	(	PUNCT
bracis-28373	68	24	type	type	NOUN
bracis-28373	68	25	ii	ii	NOUN
bracis-28373	68	26	attacks	attack	NOUN
bracis-28373	68	27	)	)	PUNCT
bracis-28373	68	28	,	,	PUNCT
bracis-28373	68	29	especially	especially	ADV
bracis-28373	68	30	in	in	ADP
bracis-28373	68	31	the	the	DET
bracis-28373	68	32	untargeted	untargeted	ADJ
bracis-28373	68	33	attack	attack	NOUN
bracis-28373	68	34	.	.	PUNCT
bracis-28373	69	1	among	among	ADP
bracis-28373	69	2	these	these	DET
bracis-28373	69	3	types	type	NOUN
bracis-28373	69	4	of	of	ADP
bracis-28373	69	5	attacks	attack	NOUN
bracis-28373	69	6	,	,	PUNCT
bracis-28373	69	7	data	data	NOUN
bracis-28373	69	8	poisoning	poisoning	NOUN
bracis-28373	69	9	(	(	PUNCT
bracis-28373	69	10	i.e.	i.e.	X
bracis-28373	69	11	,	,	PUNCT
bracis-28373	69	12	poisoning	poisoning	NOUN
bracis-28373	69	13	in	in	ADP
bracis-28373	69	14	the	the	DET
bracis-28373	69	15	training	training	NOUN
bracis-28373	69	16	dataset	dataset	NOUN
bracis-28373	69	17	)	)	PUNCT
bracis-28373	69	18	is	be	AUX
bracis-28373	69	19	one	one	NUM
bracis-28373	69	20	of	of	ADP
bracis-28373	69	21	the	the	DET
bracis-28373	69	22	most	most	ADV
bracis-28373	69	23	common	common	ADJ
bracis-28373	69	24	forms	form	NOUN
bracis-28373	69	25	of	of	ADP
bracis-28373	69	26	poisoning	poisoning	NOUN
bracis-28373	69	27	attack	attack	NOUN
bracis-28373	69	28	.	.	PUNCT
bracis-28373	70	1	several	several	ADJ
bracis-28373	70	2	works	work	NOUN
bracis-28373	70	3	in	in	ADP
bracis-28373	70	4	the	the	DET
bracis-28373	70	5	literature	literature	NOUN
bracis-28373	70	6	propose	propose	VERB
bracis-28373	70	7	a	a	DET
bracis-28373	70	8	poisoning	poisoning	NOUN
bracis-28373	70	9	attack	attack	NOUN
bracis-28373	70	10	method	method	NOUN
bracis-28373	70	11	to	to	ADP
bracis-28373	70	12	fl	fl	NOUN
bracis-28373	70	13	models	model	NOUN
bracis-28373	70	14	to	to	PART
bracis-28373	70	15	degrade	degrade	VERB
bracis-28373	70	16	the	the	DET
bracis-28373	70	17	training	training	NOUN
bracis-28373	70	18	process	process	NOUN
bracis-28373	70	19	.	.	PUNCT
bracis-28373	71	1	zhang	zhang	PROPN
bracis-28373	71	2	et	et	PROPN
bracis-28373	71	3	al	al	PROPN
bracis-28373	71	4	.	.	PUNCT
bracis-28373	71	5	 	 	SPACE
bracis-28373	72	1	[	[	X
bracis-28373	72	2	25	25	NUM
bracis-28373	72	3	]	]	X
bracis-28373	72	4	propose	propose	VERB
bracis-28373	72	5	using	use	VERB
bracis-28373	72	6	generative	generative	ADJ
bracis-28373	72	7	adversarial	adversarial	ADJ
bracis-28373	72	8	networks	network	NOUN
bracis-28373	72	9	(	(	PUNCT
bracis-28373	72	10	gans	gan	NOUN
bracis-28373	72	11	)	)	PUNCT
bracis-28373	72	12	to	to	PART
bracis-28373	72	13	generate	generate	VERB
bracis-28373	72	14	examples	example	NOUN
bracis-28373	72	15	without	without	ADP
bracis-28373	72	16	any	any	DET
bracis-28373	72	17	assumption	assumption	NOUN
bracis-28373	72	18	on	on	ADP
bracis-28373	72	19	accessing	access	VERB
bracis-28373	72	20	the	the	DET
bracis-28373	72	21	participants	participant	NOUN
bracis-28373	72	22	’	'	PUNCT
bracis-28373	72	23	training	training	NOUN
bracis-28373	72	24	data	datum	NOUN
bracis-28373	72	25	.	.	PUNCT
bracis-28373	73	1	similarly	similarly	ADV
bracis-28373	73	2	,	,	PUNCT
bracis-28373	73	3	zhang	zhang	PROPN
bracis-28373	73	4	et	et	PROPN
bracis-28373	73	5	al	al	PROPN
bracis-28373	73	6	.	.	PUNCT
bracis-28373	73	7	 	 	SPACE
bracis-28373	74	1	[	[	X
bracis-28373	74	2	26	26	NUM
bracis-28373	74	3	]	]	PUNCT
bracis-28373	74	4	then	then	ADV
bracis-28373	74	5	inserts	insert	VERB
bracis-28373	74	6	adversarial	adversarial	ADJ
bracis-28373	74	7	poison	poison	NOUN
bracis-28373	74	8	samples	sample	NOUN
bracis-28373	74	9	assigned	assign	VERB
bracis-28373	74	10	with	with	ADP
bracis-28373	74	11	the	the	DET
bracis-28373	74	12	wrong	wrong	ADJ
bracis-28373	74	13	label	label	NOUN
bracis-28373	74	14	to	to	ADP
bracis-28373	74	15	the	the	DET
bracis-28373	74	16	local	local	ADJ
bracis-28373	74	17	training	training	NOUN
bracis-28373	74	18	dataset	dataset	VERB
bracis-28373	74	19	to	to	PART
bracis-28373	74	20	degrade	degrade	VERB
bracis-28373	74	21	the	the	DET
bracis-28373	74	22	aggregate	aggregate	ADJ
bracis-28373	74	23	model	model	NOUN
bracis-28373	74	24	.	.	PUNCT
bracis-28373	75	1	sun	sun	PROPN
bracis-28373	75	2	et	et	PROPN
bracis-28373	75	3	al	al	PROPN
bracis-28373	75	4	.	.	PUNCT
bracis-28373	75	5	 	 	SPACE
bracis-28373	76	1	[	[	X
bracis-28373	76	2	19	19	NUM
bracis-28373	76	3	]	]	PUNCT
bracis-28373	76	4	studies	study	NOUN
bracis-28373	76	5	the	the	DET
bracis-28373	76	6	vulnerability	vulnerability	NOUN
bracis-28373	76	7	of	of	ADP
bracis-28373	76	8	federated	federated	ADJ
bracis-28373	76	9	learning	learning	NOUN
bracis-28373	76	10	models	model	NOUN
bracis-28373	76	11	in	in	ADP
bracis-28373	76	12	iot	iot	NOUN
bracis-28373	76	13	systems	system	NOUN
bracis-28373	76	14	.	.	PUNCT
bracis-28373	77	1	thus	thus	ADV
bracis-28373	77	2	,	,	PUNCT
bracis-28373	77	3	the	the	DET
bracis-28373	77	4	authors	author	NOUN
bracis-28373	77	5	use	use	VERB
bracis-28373	77	6	a	a	DET
bracis-28373	77	7	bilevel	bilevel	ADJ
bracis-28373	77	8	optimization	optimization	NOUN
bracis-28373	77	9	consideration	consideration	NOUN
bracis-28373	77	10	,	,	PUNCT
bracis-28373	77	11	which	which	PRON
bracis-28373	77	12	injects	inject	VERB
bracis-28373	77	13	poisoned	poison	VERB
bracis-28373	77	14	data	data	NOUN
bracis-28373	77	15	samples	sample	NOUN
bracis-28373	77	16	to	to	PART
bracis-28373	77	17	maximize	maximize	VERB
bracis-28373	77	18	the	the	DET
bracis-28373	77	19	deterioration	deterioration	NOUN
bracis-28373	77	20	of	of	ADP
bracis-28373	77	21	the	the	DET
bracis-28373	77	22	aggregate	aggregate	ADJ
bracis-28373	77	23	model	model	NOUN
bracis-28373	77	24	.	.	PUNCT
bracis-28373	78	1	in	in	ADP
bracis-28373	78	2	addition	addition	NOUN
bracis-28373	78	3	,	,	PUNCT
bracis-28373	78	4	defense	defense	NOUN
bracis-28373	78	5	mechanisms	mechanism	NOUN
bracis-28373	78	6	for	for	ADP
bracis-28373	78	7	distributed	distribute	VERB
bracis-28373	78	8	poisoning	poisoning	NOUN
bracis-28373	78	9	attacks	attack	NOUN
bracis-28373	78	10	typically	typically	ADV
bracis-28373	78	11	draw	draw	VERB
bracis-28373	78	12	ideas	idea	NOUN
bracis-28373	78	13	from	from	ADP
bracis-28373	78	14	robust	robust	ADJ
bracis-28373	78	15	estimation	estimation	NOUN
bracis-28373	78	16	and	and	CCONJ
bracis-28373	78	17	anomaly	anomaly	NOUN
bracis-28373	78	18	detection	detection	NOUN
bracis-28373	78	19	 	 	SPACE
bracis-28373	79	1	[	[	X
bracis-28373	79	2	1	1	NUM
bracis-28373	79	3	,	,	PUNCT
bracis-28373	79	4	18	18	NUM
bracis-28373	79	5	]	]	PUNCT
bracis-28373	79	6	.	.	PUNCT
bracis-28373	80	1	some	some	DET
bracis-28373	80	2	works	work	NOUN
bracis-28373	80	3	are	be	AUX
bracis-28373	80	4	based	base	VERB
bracis-28373	80	5	on	on	ADP
bracis-28373	80	6	aggregation	aggregation	NOUN
bracis-28373	80	7	functions	function	NOUN
bracis-28373	80	8	robust	robust	ADJ
bracis-28373	80	9	to	to	ADP
bracis-28373	80	10	outliers	outlier	NOUN
bracis-28373	80	11	,	,	PUNCT
bracis-28373	80	12	such	such	ADJ
bracis-28373	80	13	as	as	ADP
bracis-28373	80	14	median	median	NOUN
bracis-28373	80	15	 	 	SPACE
bracis-28373	81	1	[	[	X
bracis-28373	81	2	22	22	NUM
bracis-28373	81	3	]	]	PUNCT
bracis-28373	81	4	,	,	PUNCT
bracis-28373	81	5	mean	mean	VERB
bracis-28373	81	6	with	with	ADP
bracis-28373	81	7	exclusion	exclusion	NOUN
bracis-28373	81	8	 	 	SPACE
bracis-28373	82	1	[	[	X
bracis-28373	82	2	23	23	NUM
bracis-28373	82	3	]	]	PUNCT
bracis-28373	82	4	,	,	PUNCT
bracis-28373	82	5	geometric	geometric	ADJ
bracis-28373	82	6	mean	mean	NOUN
bracis-28373	82	7	 	 	SPACE
bracis-28373	83	1	[	[	X
bracis-28373	83	2	16	16	NUM
bracis-28373	83	3	]	]	PUNCT
bracis-28373	83	4	,	,	PUNCT
bracis-28373	83	5	and	and	CCONJ
bracis-28373	83	6	clustering	clustering	NOUN
bracis-28373	83	7	of	of	ADP
bracis-28373	83	8	nearby	nearby	ADJ
bracis-28373	83	9	gradients	gradient	NOUN
bracis-28373	83	10	 	 	SPACE
bracis-28373	84	1	[	[	X
bracis-28373	84	2	4	4	NUM
bracis-28373	84	3	]	]	PUNCT
bracis-28373	84	4	.	.	PUNCT
bracis-28373	85	1	additionally	additionally	ADV
bracis-28373	85	2	,	,	PUNCT
bracis-28373	85	3	assuming	assume	VERB
bracis-28373	85	4	scenarios	scenario	NOUN
bracis-28373	85	5	,	,	PUNCT
bracis-28373	85	6	where	where	SCONJ
bracis-28373	85	7	all	all	DET
bracis-28373	85	8	clients	client	NOUN
bracis-28373	85	9	train	train	VERB
bracis-28373	85	10	the	the	DET
bracis-28373	85	11	network	network	NOUN
bracis-28373	85	12	model	model	NOUN
bracis-28373	85	13	but	but	CCONJ
bracis-28373	85	14	use	use	VERB
bracis-28373	85	15	their	their	PRON
bracis-28373	85	16	data	datum	NOUN
bracis-28373	85	17	is	be	AUX
bracis-28373	85	18	paramount	paramount	ADJ
bracis-28373	85	19	.	.	PUNCT
bracis-28373	86	1	more	more	ADV
bracis-28373	86	2	often	often	ADV
bracis-28373	86	3	than	than	ADP
bracis-28373	86	4	not	not	PART
bracis-28373	86	5	,	,	PUNCT
bracis-28373	86	6	we	we	PRON
bracis-28373	86	7	observe	observe	VERB
bracis-28373	86	8	that	that	SCONJ
bracis-28373	86	9	data	data	NOUN
bracis-28373	86	10	models	model	NOUN
bracis-28373	86	11	differ	differ	VERB
bracis-28373	86	12	across	across	ADP
bracis-28373	86	13	clients	client	NOUN
bracis-28373	86	14	.	.	PUNCT
bracis-28373	87	1	therefore	therefore	ADV
bracis-28373	87	2	,	,	PUNCT
bracis-28373	87	3	the	the	DET
bracis-28373	87	4	resulting	result	VERB
bracis-28373	87	5	models	model	NOUN
bracis-28373	87	6	will	will	AUX
bracis-28373	87	7	be	be	AUX
bracis-28373	87	8	abstractions	abstraction	NOUN
bracis-28373	87	9	of	of	ADP
bracis-28373	87	10	different	different	ADJ
bracis-28373	87	11	real	real	ADJ
bracis-28373	87	12	-	-	PUNCT
bracis-28373	87	13	world	world	NOUN
bracis-28373	87	14	conditions	condition	NOUN
bracis-28373	87	15	.	.	PUNCT
bracis-28373	88	1	ultimately	ultimately	ADV
bracis-28373	88	2	,	,	PUNCT
bracis-28373	88	3	we	we	PRON
bracis-28373	88	4	need	need	VERB
bracis-28373	88	5	to	to	PART
bracis-28373	88	6	propose	propose	VERB
bracis-28373	88	7	solutions	solution	NOUN
bracis-28373	88	8	that	that	PRON
bracis-28373	88	9	handle	handle	VERB
bracis-28373	88	10	such	such	ADJ
bracis-28373	88	11	situations	situation	NOUN
bracis-28373	88	12	bearing	bear	VERB
bracis-28373	88	13	in	in	ADP
bracis-28373	88	14	mind	mind	NOUN
bracis-28373	88	15	the	the	DET
bracis-28373	88	16	challenges	challenge	NOUN
bracis-28373	88	17	of	of	ADP
bracis-28373	88	18	accounting	account	VERB
bracis-28373	88	19	for	for	ADP
bracis-28373	88	20	such	such	ADJ
bracis-28373	88	21	differences	difference	NOUN
bracis-28373	88	22	without	without	ADP
bracis-28373	88	23	considering	consider	VERB
bracis-28373	88	24	them	they	PRON
bracis-28373	88	25	malicious	malicious	ADJ
bracis-28373	88	26	,	,	PUNCT
bracis-28373	88	27	especially	especially	ADV
bracis-28373	88	28	when	when	SCONJ
bracis-28373	88	29	only	only	ADV
bracis-28373	88	30	a	a	DET
bracis-28373	88	31	small	small	ADJ
bracis-28373	88	32	subset	subset	NOUN
bracis-28373	88	33	of	of	ADP
bracis-28373	88	34	clients	client	NOUN
bracis-28373	88	35	present	present	VERB
bracis-28373	88	36	data	data	NOUN
bracis-28373	88	37	models	model	NOUN
bracis-28373	88	38	apart	apart	ADV
bracis-28373	88	39	from	from	ADP
bracis-28373	88	40	the	the	DET
bracis-28373	88	41	majority	majority	NOUN
bracis-28373	88	42	.	.	PUNCT
bracis-28373	89	1	3	3	NUM
bracis-28373	89	2	our	our	PRON
bracis-28373	89	3	proposal	proposal	NOUN
bracis-28373	89	4	3.1	3.1	NUM
bracis-28373	89	5	bayesian	bayesian	NOUN
bracis-28373	89	6	neural	neural	ADJ
bracis-28373	89	7	network	network	NOUN
bracis-28373	89	8	a	a	DET
bracis-28373	89	9	bnn	bnn	PROPN
bracis-28373	89	10	is	be	AUX
bracis-28373	89	11	a	a	DET
bracis-28373	89	12	neural	neural	ADJ
bracis-28373	89	13	network	network	NOUN
bracis-28373	89	14	\(f(\textbf{x	\(f(\textbf{x	NOUN
bracis-28373	89	15	}	}	PUNCT
bracis-28373	89	16	,	,	PUNCT
bracis-28373	89	17	\textbf{w})\	\textbf{w})\	NOUN
bracis-28373	89	18	)	)	PUNCT
bracis-28373	89	19	that	that	PRON
bracis-28373	89	20	maps	map	VERB
bracis-28373	89	21	inputs	input	NOUN
bracis-28373	89	22	\(\textbf{x}\	\(\textbf{x}\	NOUN
bracis-28373	89	23	)	)	PUNCT
bracis-28373	89	24	to	to	ADP
bracis-28373	89	25	outputs	outputs	PROPN
bracis-28373	89	26	y	y	PROPN
bracis-28373	89	27	,	,	PUNCT
bracis-28373	89	28	where	where	SCONJ
bracis-28373	89	29	\(\textbf{w	\(\textbf{w	ADJ
bracis-28373	89	30	}	}	PUNCT
bracis-28373	89	31	\in	\in	ADJ
bracis-28373	89	32	\mathbb	\mathbb	PROPN
bracis-28373	89	33	{	{	PUNCT
bracis-28373	89	34	r}^{m}\	r}^{m}\	NOUN
bracis-28373	89	35	)	)	PUNCT
bracis-28373	89	36	is	be	AUX
bracis-28373	89	37	a	a	DET
bracis-28373	89	38	vector	vector	NOUN
bracis-28373	89	39	of	of	ADP
bracis-28373	89	40	random	random	ADJ
bracis-28373	89	41	variables	variable	NOUN
bracis-28373	89	42	representing	represent	VERB
bracis-28373	89	43	the	the	DET
bracis-28373	89	44	weights	weight	NOUN
bracis-28373	89	45	and	and	CCONJ
bracis-28373	89	46	biases	bias	NOUN
bracis-28373	89	47	of	of	ADP
bracis-28373	89	48	the	the	DET
bracis-28373	89	49	network	network	NOUN
bracis-28373	89	50	.	.	PUNCT
bracis-28373	90	1	the	the	DET
bracis-28373	90	2	bnn	bnn	PROPN
bracis-28373	90	3	assumes	assume	VERB
bracis-28373	90	4	a	a	DET
bracis-28373	90	5	prior	prior	ADJ
bracis-28373	90	6	distribution	distribution	NOUN
bracis-28373	90	7	over	over	ADP
bracis-28373	90	8	\(\textbf{w}\	\(\textbf{w}\	NUM
bracis-28373	90	9	)	)	PUNCT
bracis-28373	90	10	,	,	PUNCT
bracis-28373	90	11	denoted	denote	VERB
bracis-28373	90	12	\(p(\textbf{w})\	\(p(\textbf{w})\	ADV
bracis-28373	90	13	)	)	PUNCT
bracis-28373	90	14	,	,	PUNCT
bracis-28373	90	15	and	and	CCONJ
bracis-28373	90	16	learns	learn	VERB
bracis-28373	90	17	a	a	DET
bracis-28373	90	18	posterior	posterior	ADJ
bracis-28373	90	19	distribution	distribution	NOUN
bracis-28373	90	20	\(p(\textbf{w}\mid	\(p(\textbf{w}\mid	PROPN
bracis-28373	90	21	\mathcal	\mathcal	PROPN
bracis-28373	90	22	{	{	PUNCT
bracis-28373	90	23	d})\	d})\	NOUN
bracis-28373	90	24	)	)	PUNCT
bracis-28373	90	25	over	over	ADP
bracis-28373	90	26	the	the	DET
bracis-28373	90	27	weights	weight	NOUN
bracis-28373	90	28	and	and	CCONJ
bracis-28373	90	29	biases	bias	NOUN
bracis-28373	90	30	given	give	VERB
bracis-28373	90	31	the	the	DET
bracis-28373	90	32	training	training	NOUN
bracis-28373	90	33	data	datum	NOUN
bracis-28373	90	34	\(\mathcal	\(\mathcal	ADJ
bracis-28373	90	35	{	{	PUNCT
bracis-28373	90	36	d	d	NOUN
bracis-28373	90	37	}	}	PUNCT
bracis-28373	90	38	=	=	PUNCT
bracis-28373	90	39	\{(\textbf{x}_i	\{(\textbf{x}_i	PROPN
bracis-28373	90	40	,	,	PUNCT
bracis-28373	90	41	y_i)\}_{i=1}^n\	y_i)\}_{i=1}^n\	PROPN
bracis-28373	90	42	)	)	PUNCT
bracis-28373	90	43	.	.	PUNCT
bracis-28373	91	1	thus	thus	ADV
bracis-28373	91	2	,	,	PUNCT
bracis-28373	91	3	for	for	ADP
bracis-28373	91	4	a	a	DET
bracis-28373	91	5	dataset	dataset	NOUN
bracis-28373	91	6	\(\mathcal	\(\mathcal	ADJ
bracis-28373	91	7	{	{	PUNCT
bracis-28373	91	8	d}\	d}\	PROPN
bracis-28373	91	9	)	)	PUNCT
bracis-28373	91	10	,	,	PUNCT
bracis-28373	91	11	we	we	PRON
bracis-28373	91	12	have	have	VERB
bracis-28373	91	13	\(p(\mathcal	\(p(\mathcal	ADJ
bracis-28373	91	14	{	{	PUNCT
bracis-28373	91	15	d	d	NOUN
bracis-28373	91	16	}	}	PUNCT
bracis-28373	91	17	\mid	\mid	ADP
bracis-28373	91	18	{	{	PUNCT
bracis-28373	91	19	\textbf	\textbf	PROPN
bracis-28373	91	20	{	{	PUNCT
bracis-28373	91	21	w	w	NOUN
bracis-28373	91	22	}	}	PUNCT
bracis-28373	91	23	}	}	PUNCT
bracis-28373	91	24	)	)	PUNCT
bracis-28373	92	1	=	=	PUNCT
bracis-28373	92	2	\varpi	\varpi	PROPN
bracis-28373	92	3	_	_	PUNCT
bracis-28373	92	4	{	{	PUNCT
bracis-28373	92	5	i=1}^n	i=1}^n	X
bracis-28373	92	6	p(y_i	p(y_i	NOUN
bracis-28373	92	7	\mid	\mid	ADP
bracis-28373	92	8	f({\textbf	f({\textbf	PROPN
bracis-28373	92	9	{	{	PUNCT
bracis-28373	92	10	x}}_i	x}}_i	PROPN
bracis-28373	92	11	,	,	PUNCT
bracis-28373	92	12	{	{	PUNCT
bracis-28373	92	13	\textbf	\textbf	PROPN
bracis-28373	92	14	{	{	PUNCT
bracis-28373	92	15	w}}))\	w}}))\	PROPN
bracis-28373	92	16	)	)	PUNCT
bracis-28373	92	17	.	.	PUNCT
bracis-28373	93	1	bayesian	bayesian	NOUN
bracis-28373	93	2	inference	inference	NOUN
bracis-28373	93	3	techniques	technique	NOUN
bracis-28373	93	4	such	such	ADJ
bracis-28373	93	5	as	as	ADP
bracis-28373	93	6	markov	markov	NOUN
bracis-28373	93	7	chain	chain	NOUN
bracis-28373	93	8	monte	monte	PROPN
bracis-28373	93	9	carlo	carlo	PROPN
bracis-28373	93	10	(	(	PUNCT
bracis-28373	93	11	mcmc	mcmc	PROPN
bracis-28373	93	12	)	)	PUNCT
bracis-28373	93	13	,	,	PUNCT
bracis-28373	93	14	variational	variational	ADJ
bracis-28373	93	15	inference	inference	NOUN
bracis-28373	93	16	,	,	PUNCT
bracis-28373	93	17	and	and	CCONJ
bracis-28373	93	18	laplace	laplace	NOUN
bracis-28373	93	19	approximation	approximation	NOUN
bracis-28373	93	20	can	can	AUX
bracis-28373	93	21	approximate	approximate	VERB
bracis-28373	93	22	the	the	DET
bracis-28373	93	23	posterior	posterior	ADJ
bracis-28373	93	24	distribution	distribution	NOUN
bracis-28373	93	25	.	.	PUNCT
bracis-28373	94	1	given	give	VERB
bracis-28373	94	2	the	the	DET
bracis-28373	94	3	posterior	posterior	ADJ
bracis-28373	94	4	distribution	distribution	NOUN
bracis-28373	94	5	,	,	PUNCT
bracis-28373	94	6	the	the	DET
bracis-28373	94	7	network	network	NOUN
bracis-28373	94	8	can	can	AUX
bracis-28373	94	9	make	make	VERB
bracis-28373	94	10	predictions	prediction	NOUN
bracis-28373	94	11	by	by	ADP
bracis-28373	94	12	computing	compute	VERB
bracis-28373	94	13	the	the	DET
bracis-28373	94	14	predictive	predictive	ADJ
bracis-28373	94	15	distribution	distribution	NOUN
bracis-28373	94	16	\(p(y\mid	\(p(y\mid	PROPN
bracis-28373	94	17	\textbf{x	\textbf{x	NOUN
bracis-28373	94	18	}	}	PUNCT
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bracis-28373	94	21	{	{	PUNCT
bracis-28373	94	22	d})\	d})\	NOUN
bracis-28373	94	23	)	)	PUNCT
bracis-28373	94	24	over	over	ADP
bracis-28373	94	25	the	the	DET
bracis-28373	94	26	output	output	NOUN
bracis-28373	94	27	given	give	VERB
bracis-28373	94	28	the	the	DET
bracis-28373	94	29	input	input	NOUN
bracis-28373	94	30	and	and	CCONJ
bracis-28373	94	31	the	the	DET
bracis-28373	94	32	training	training	NOUN
bracis-28373	94	33	data	datum	NOUN
bracis-28373	94	34	.	.	PUNCT
bracis-28373	95	1	the	the	DET
bracis-28373	95	2	bnn	bnn	PROPN
bracis-28373	95	3	approach	approach	NOUN
bracis-28373	95	4	provides	provide	VERB
bracis-28373	95	5	a	a	DET
bracis-28373	95	6	probabilistic	probabilistic	ADJ
bracis-28373	95	7	framework	framework	NOUN
bracis-28373	95	8	for	for	ADP
bracis-28373	95	9	modeling	model	VERB
bracis-28373	95	10	uncertainty	uncertainty	NOUN
bracis-28373	95	11	in	in	ADP
bracis-28373	95	12	the	the	DET
bracis-28373	95	13	network	network	NOUN
bracis-28373	95	14	’s	’s	PART
bracis-28373	95	15	predictions	prediction	NOUN
bracis-28373	95	16	and	and	CCONJ
bracis-28373	95	17	can	can	AUX
bracis-28373	95	18	be	be	AUX
bracis-28373	95	19	particularly	particularly	ADV
bracis-28373	95	20	useful	useful	ADJ
bracis-28373	95	21	in	in	ADP
bracis-28373	95	22	applications	application	NOUN
bracis-28373	95	23	where	where	SCONJ
bracis-28373	95	24	knowing	know	VERB
bracis-28373	95	25	the	the	DET
bracis-28373	95	26	level	level	NOUN
bracis-28373	95	27	of	of	ADP
bracis-28373	95	28	uncertainty	uncertainty	NOUN
bracis-28373	95	29	is	be	AUX
bracis-28373	95	30	essential	essential	ADJ
bracis-28373	95	31	.	.	PUNCT
bracis-28373	96	1	in	in	ADP
bracis-28373	96	2	addition	addition	NOUN
bracis-28373	96	3	,	,	PUNCT
bracis-28373	96	4	the	the	DET
bracis-28373	96	5	regularization	regularization	NOUN
bracis-28373	96	6	effect	effect	NOUN
bracis-28373	96	7	of	of	ADP
bracis-28373	96	8	the	the	DET
bracis-28373	96	9	prior	prior	ADJ
bracis-28373	96	10	distribution	distribution	NOUN
bracis-28373	96	11	can	can	AUX
bracis-28373	96	12	also	also	ADV
bracis-28373	96	13	prevent	prevent	VERB
bracis-28373	96	14	overfitting	overfitting	NOUN
bracis-28373	96	15	and	and	CCONJ
bracis-28373	96	16	improve	improve	VERB
bracis-28373	96	17	the	the	DET
bracis-28373	96	18	generalization	generalization	NOUN
bracis-28373	96	19	performance	performance	NOUN
bracis-28373	96	20	of	of	ADP
bracis-28373	96	21	the	the	DET
bracis-28373	96	22	network	network	NOUN
bracis-28373	96	23	.	.	PUNCT
bracis-28373	97	1	3.2	3.2	NUM
bracis-28373	97	2	laplace	laplace	NOUN
bracis-28373	97	3	approximation	approximation	NOUN
bracis-28373	97	4	in	in	ADP
bracis-28373	97	5	bayesian	bayesian	NOUN
bracis-28373	97	6	inference	inference	NOUN
bracis-28373	97	7	,	,	PUNCT
bracis-28373	97	8	we	we	PRON
bracis-28373	97	9	are	be	AUX
bracis-28373	97	10	interested	interested	ADJ
bracis-28373	97	11	in	in	ADP
bracis-28373	97	12	computing	compute	VERB
bracis-28373	97	13	the	the	DET
bracis-28373	97	14	posterior	posterior	ADJ
bracis-28373	97	15	distribution	distribution	NOUN
bracis-28373	97	16	of	of	ADP
bracis-28373	97	17	the	the	DET
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bracis-28373	97	19	parameters	parameter	NOUN
bracis-28373	97	20	\({\textbf	\({\textbf	PROPN
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bracis-28373	97	22	w}}\	w}}\	NOUN
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bracis-28373	97	24	given	give	VERB
bracis-28373	97	25	the	the	DET
bracis-28373	97	26	observed	observe	VERB
bracis-28373	97	27	data	datum	NOUN
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bracis-28373	98	29	p({\textbf	p({\textbf	NOUN
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bracis-28373	98	54	likelihood	likelihood	NOUN
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bracis-28373	98	56	\(p({\textbf	\(p({\textbf	PROPN
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bracis-28373	98	60	is	be	AUX
bracis-28373	98	61	the	the	DET
bracis-28373	98	62	prior	prior	ADJ
bracis-28373	98	63	distribution	distribution	NOUN
bracis-28373	98	64	of	of	ADP
bracis-28373	98	65	the	the	DET
bracis-28373	98	66	parameters	parameter	NOUN
bracis-28373	98	67	,	,	PUNCT
bracis-28373	98	68	and	and	CCONJ
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bracis-28373	98	70	integral	integral	ADJ
bracis-28373	98	71	in	in	ADP
bracis-28373	98	72	the	the	DET
bracis-28373	98	73	denominator	denominator	NOUN
bracis-28373	98	74	is	be	AUX
bracis-28373	98	75	the	the	DET
bracis-28373	98	76	normalization	normalization	NOUN
bracis-28373	98	77	constant	constant	ADJ
bracis-28373	98	78	.	.	PUNCT
bracis-28373	99	1	unfortunately	unfortunately	ADV
bracis-28373	99	2	,	,	PUNCT
bracis-28373	99	3	\(\int	\(\int	NOUN
bracis-28373	99	4	p(\mathcal	p(\mathcal	ADJ
bracis-28373	99	5	{	{	PUNCT
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bracis-28373	99	7	}	}	PUNCT
bracis-28373	99	8	\mid	\mid	ADP
bracis-28373	99	9	{	{	PUNCT
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bracis-28373	99	11	{	{	PUNCT
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bracis-28373	99	16	p({\textbf	p({\textbf	NOUN
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bracis-28373	99	20	w}}\	w}}\	NOUN
bracis-28373	99	21	)	)	PUNCT
bracis-28373	99	22	is	be	AUX
bracis-28373	99	23	often	often	ADV
bracis-28373	99	24	intractable	intractable	ADJ
bracis-28373	99	25	for	for	ADP
bracis-28373	99	26	complex	complex	ADJ
bracis-28373	99	27	models	model	NOUN
bracis-28373	99	28	(	(	PUNCT
bracis-28373	99	29	as	as	ADP
bracis-28373	99	30	neural	neural	ADJ
bracis-28373	99	31	networks	network	NOUN
bracis-28373	99	32	)	)	PUNCT
bracis-28373	99	33	,	,	PUNCT
bracis-28373	99	34	and	and	CCONJ
bracis-28373	99	35	we	we	PRON
bracis-28373	99	36	need	need	VERB
bracis-28373	99	37	to	to	PART
bracis-28373	99	38	resort	resort	VERB
bracis-28373	99	39	to	to	ADP
bracis-28373	99	40	approximate	approximate	ADJ
bracis-28373	99	41	inference	inference	NOUN
bracis-28373	99	42	methods	method	NOUN
bracis-28373	99	43	.	.	PUNCT
bracis-28373	100	1	one	one	NUM
bracis-28373	100	2	such	such	ADJ
bracis-28373	100	3	method	method	NOUN
bracis-28373	100	4	is	be	AUX
bracis-28373	100	5	the	the	DET
bracis-28373	100	6	laplace	laplace	NOUN
bracis-28373	100	7	approximation	approximation	NOUN
bracis-28373	100	8	,	,	PUNCT
bracis-28373	100	9	which	which	PRON
bracis-28373	100	10	approximates	approximate	VERB
bracis-28373	100	11	the	the	DET
bracis-28373	100	12	posterior	posterior	ADJ
bracis-28373	100	13	distribution	distribution	NOUN
bracis-28373	100	14	with	with	ADP
bracis-28373	100	15	a	a	DET
bracis-28373	100	16	gaussian	gaussian	ADJ
bracis-28373	100	17	distribution	distribution	NOUN
bracis-28373	100	18	centered	center	VERB
bracis-28373	100	19	at	at	ADP
bracis-28373	100	20	the	the	DET
bracis-28373	100	21	mode	mode	NOUN
bracis-28373	100	22	of	of	ADP
bracis-28373	100	23	the	the	DET
bracis-28373	100	24	posterior	posterior	NOUN
bracis-28373	100	25	,	,	PUNCT
bracis-28373	100	26	\({\textbf	\({\textbf	PROPN
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bracis-28373	100	30	(	(	PUNCT
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bracis-28373	100	32	a	a	DET
bracis-28373	100	33	posterior	posterior	NOUN
bracis-28373	100	34	)	)	PUNCT
bracis-28373	100	35	,	,	PUNCT
bracis-28373	100	36	and	and	CCONJ
bracis-28373	100	37	with	with	ADP
bracis-28373	100	38	a	a	DET
bracis-28373	100	39	covariance	covariance	NOUN
bracis-28373	100	40	matrix	matrix	NOUN
bracis-28373	100	41	given	give	VERB
bracis-28373	100	42	by	by	ADP
bracis-28373	100	43	the	the	DET
bracis-28373	100	44	inverse	inverse	ADJ
bracis-28373	100	45	hessian	hessian	NOUN
bracis-28373	100	46	matrix	matrix	NOUN
bracis-28373	100	47	evaluated	evaluate	VERB
bracis-28373	100	48	at	at	ADP
bracis-28373	100	49	\({\textbf	\({\textbf	PROPN
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bracis-28373	101	2	derive	derive	VERB
bracis-28373	101	3	the	the	DET
bracis-28373	101	4	laplace	laplace	NOUN
bracis-28373	101	5	approximation	approximation	NOUN
bracis-28373	101	6	,	,	PUNCT
bracis-28373	101	7	we	we	PRON
bracis-28373	101	8	start	start	VERB
bracis-28373	101	9	by	by	ADP
bracis-28373	101	10	manipulating	manipulate	VERB
bracis-28373	101	11	the	the	DET
bracis-28373	101	12	integral	integral	NOUN
bracis-28373	101	13	in	in	ADP
bracis-28373	101	14	the	the	DET
bracis-28373	101	15	denominator	denominator	NOUN
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bracis-28373	110	42	|{\textbf	|{\textbf	NOUN
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bracis-28373	111	15	w	w	NOUN
bracis-28373	111	16	}	}	PUNCT
bracis-28373	111	17	}	}	PUNCT
bracis-28373	111	18	\mid	\mid	ADP
bracis-28373	111	19	\mathcal	\mathcal	PROPN
bracis-28373	111	20	{	{	PUNCT
bracis-28373	111	21	d	d	NOUN
bracis-28373	111	22	}	}	PUNCT
bracis-28373	111	23	)	)	PUNCT
bracis-28373	112	1	\approx	\approx	PROPN
bracis-28373	112	2	\mathcal	\mathcal	PROPN
bracis-28373	112	3	{	{	PUNCT
bracis-28373	112	4	n	n	CCONJ
bracis-28373	112	5	}	}	PUNCT
bracis-28373	112	6	(	(	PUNCT
bracis-28373	112	7	{	{	PUNCT
bracis-28373	112	8	\textbf	\textbf	PROPN
bracis-28373	112	9	{	{	PUNCT
bracis-28373	112	10	w	w	NOUN
bracis-28373	112	11	}	}	PUNCT
bracis-28373	112	12	}	}	PUNCT
bracis-28373	112	13	\mid	\mid	ADP
bracis-28373	112	14	{	{	PUNCT
bracis-28373	112	15	\textbf	\textbf	PROPN
bracis-28373	112	16	{	{	PUNCT
bracis-28373	112	17	w}}_{map	w}}_{map	NOUN
bracis-28373	112	18	}	}	PUNCT
bracis-28373	112	19	,	,	PUNCT
bracis-28373	112	20	{	{	PUNCT
bracis-28373	112	21	\textbf	\textbf	PROPN
bracis-28373	112	22	{	{	PUNCT
bracis-28373	112	23	h}}_{map}^{-1	h}}_{map}^{-1	NOUN
bracis-28373	112	24	}	}	PUNCT
bracis-28373	112	25	)	)	PUNCT
bracis-28373	112	26	,	,	PUNCT
bracis-28373	112	27	\	\	PROPN
bracis-28373	112	28	)	)	PUNCT
bracis-28373	112	29	where	where	SCONJ
bracis-28373	112	30	\(\mathcal	\(\mathcal	ADJ
bracis-28373	112	31	{	{	PUNCT
bracis-28373	112	32	n	n	CCONJ
bracis-28373	112	33	}	}	PUNCT
bracis-28373	112	34	(	(	PUNCT
bracis-28373	112	35	{	{	PUNCT
bracis-28373	112	36	\textbf	\textbf	PROPN
bracis-28373	112	37	{	{	PUNCT
bracis-28373	112	38	w	w	NOUN
bracis-28373	112	39	}	}	PUNCT
bracis-28373	112	40	}	}	PUNCT
bracis-28373	112	41	\mid	\mid	ADP
bracis-28373	112	42	{	{	PUNCT
bracis-28373	112	43	\textbf	\textbf	PROPN
bracis-28373	112	44	{	{	PUNCT
bracis-28373	112	45	w}}_{map	w}}_{map	NOUN
bracis-28373	112	46	}	}	PUNCT
bracis-28373	112	47	,	,	PUNCT
bracis-28373	112	48	{	{	PUNCT
bracis-28373	112	49	\textbf	\textbf	PROPN
bracis-28373	112	50	{	{	PUNCT
bracis-28373	112	51	h}}_{map}^{-1})\	h}}_{map}^{-1})\	PROPN
bracis-28373	112	52	)	)	PUNCT
bracis-28373	112	53	denotes	denote	VERB
bracis-28373	112	54	a	a	DET
bracis-28373	112	55	multivariate	multivariate	NOUN
bracis-28373	112	56	gaussian	gaussian	ADJ
bracis-28373	112	57	distribution	distribution	NOUN
bracis-28373	112	58	with	with	ADP
bracis-28373	112	59	mean	mean	PROPN
bracis-28373	112	60	\({\textbf	\({\textbf	PROPN
bracis-28373	112	61	{	{	PUNCT
bracis-28373	112	62	w}}_{map}\	w}}_{map}\	NOUN
bracis-28373	112	63	)	)	PUNCT
bracis-28373	112	64	and	and	CCONJ
bracis-28373	112	65	covariance	covariance	NOUN
bracis-28373	112	66	matrix	matrix	NOUN
bracis-28373	112	67	\({\textbf	\({\textbf	PROPN
bracis-28373	112	68	{	{	PUNCT
bracis-28373	112	69	h}}_{map}^{-1}\	h}}_{map}^{-1}\	NUM
bracis-28373	112	70	)	)	PUNCT
bracis-28373	112	71	 	 	SPACE
bracis-28373	113	1	[	[	X
bracis-28373	113	2	11	11	NUM
bracis-28373	113	3	]	]	PUNCT
bracis-28373	113	4	.	.	PUNCT
bracis-28373	114	1	therefore	therefore	ADV
bracis-28373	114	2	,	,	PUNCT
bracis-28373	114	3	the	the	DET
bracis-28373	114	4	laplace	laplace	NOUN
bracis-28373	114	5	approximation	approximation	NOUN
bracis-28373	114	6	allows	allow	VERB
bracis-28373	114	7	us	we	PRON
bracis-28373	114	8	to	to	PART
bracis-28373	114	9	approximate	approximate	VERB
bracis-28373	114	10	the	the	DET
bracis-28373	114	11	posterior	posterior	ADJ
bracis-28373	114	12	distribution	distribution	NOUN
bracis-28373	114	13	of	of	ADP
bracis-28373	114	14	the	the	DET
bracis-28373	114	15	weights	weight	NOUN
bracis-28373	114	16	as	as	ADP
bracis-28373	114	17	a	a	DET
bracis-28373	114	18	gaussian	gaussian	ADJ
bracis-28373	114	19	distribution	distribution	NOUN
bracis-28373	114	20	,	,	PUNCT
bracis-28373	114	21	which	which	PRON
bracis-28373	114	22	can	can	AUX
bracis-28373	114	23	be	be	AUX
bracis-28373	114	24	more	more	ADV
bracis-28373	114	25	computationally	computationally	ADV
bracis-28373	114	26	efficient	efficient	ADJ
bracis-28373	114	27	than	than	ADP
bracis-28373	114	28	the	the	DET
bracis-28373	114	29	full	full	ADJ
bracis-28373	114	30	posterior	posterior	ADJ
bracis-28373	114	31	distribution	distribution	NOUN
bracis-28373	114	32	.	.	PUNCT
bracis-28373	115	1	fig	fig	NOUN
bracis-28373	115	2	.	.	PUNCT
bracis-28373	116	1	2	2	X
bracis-28373	116	2	.	.	X
bracis-28373	116	3	illustration	illustration	NOUN
bracis-28373	116	4	of	of	ADP
bracis-28373	116	5	the	the	DET
bracis-28373	116	6	laplace	laplace	NOUN
bracis-28373	116	7	approximation	approximation	NOUN
bracis-28373	116	8	applied	apply	VERB
bracis-28373	116	9	to	to	ADP
bracis-28373	116	10	the	the	DET
bracis-28373	116	11	distribution	distribution	NOUN
bracis-28373	116	12	\(p(z	\(p(z	PROPN
bracis-28373	116	13	)	)	PUNCT
bracis-28373	116	14	\propto	\propto	PROPN
bracis-28373	117	1	\exp	\exp	PROPN
bracis-28373	117	2	\left	\left	PROPN
bracis-28373	117	3	(	(	PUNCT
bracis-28373	117	4	-z^2/2\right	-z^2/2\right	PROPN
bracis-28373	117	5	)	)	PUNCT
bracis-28373	117	6	\sigma	\sigma	PROPN
bracis-28373	117	7	(	(	PUNCT
bracis-28373	117	8	20z	20z	NOUN
bracis-28373	117	9	+	+	CCONJ
bracis-28373	117	10	4)\	4)\	NOUN
bracis-28373	117	11	)	)	PUNCT
bracis-28373	117	12	where	where	SCONJ
bracis-28373	117	13	\(\sigma	\(\sigma	NOUN
bracis-28373	117	14	(	(	PUNCT
bracis-28373	117	15	z)\	z)\	NOUN
bracis-28373	117	16	)	)	PUNCT
bracis-28373	117	17	is	be	AUX
bracis-28373	117	18	the	the	DET
bracis-28373	117	19	logistic	logistic	ADJ
bracis-28373	117	20	sigmoid	sigmoid	NOUN
bracis-28373	117	21	function	function	NOUN
bracis-28373	117	22	defined	define	VERB
bracis-28373	117	23	by	by	ADP
bracis-28373	117	24	\(\sigma	\(\sigma	NOUN
bracis-28373	117	25	(	(	PUNCT
bracis-28373	117	26	z	z	NOUN
bracis-28373	117	27	)	)	PUNCT
bracis-28373	117	28	=	=	PUNCT
bracis-28373	117	29	(	(	PUNCT
bracis-28373	117	30	1	1	NUM
bracis-28373	117	31	+	+	CCONJ
bracis-28373	117	32	e^{-z})^{-1}\	e^{-z})^{-1}\	ADJ
bracis-28373	117	33	)	)	PUNCT
bracis-28373	117	34	.	.	PUNCT
bracis-28373	118	1	figure	figure	NOUN
bracis-28373	118	2	(	(	PUNCT
bracis-28373	118	3	a	a	PRON
bracis-28373	118	4	)	)	PUNCT
bracis-28373	118	5	shows	show	VERB
bracis-28373	118	6	the	the	DET
bracis-28373	118	7	normalized	normalize	VERB
bracis-28373	118	8	distribution	distribution	NOUN
bracis-28373	118	9	p(z	p(z	NOUN
bracis-28373	118	10	)	)	PUNCT
bracis-28373	118	11	,	,	PUNCT
bracis-28373	118	12	together	together	ADV
bracis-28373	118	13	with	with	ADP
bracis-28373	118	14	the	the	DET
bracis-28373	118	15	laplace	laplace	NOUN
bracis-28373	118	16	approximation	approximation	NOUN
bracis-28373	118	17	centered	center	VERB
bracis-28373	118	18	on	on	ADP
bracis-28373	118	19	the	the	DET
bracis-28373	118	20	mode	mode	NOUN
bracis-28373	118	21	\(z_0\	\(z_0\	PROPN
bracis-28373	118	22	)	)	PUNCT
bracis-28373	118	23	of	of	ADP
bracis-28373	118	24	p(z	p(z	NOUN
bracis-28373	118	25	)	)	PUNCT
bracis-28373	118	26	.	.	PUNCT
bracis-28373	119	1	figure	figure	NOUN
bracis-28373	119	2	(	(	PUNCT
bracis-28373	119	3	b	b	NOUN
bracis-28373	119	4	)	)	PUNCT
bracis-28373	119	5	shows	show	VERB
bracis-28373	119	6	the	the	DET
bracis-28373	119	7	negative	negative	ADJ
bracis-28373	119	8	logarithms	logarithm	NOUN
bracis-28373	119	9	of	of	ADP
bracis-28373	119	10	the	the	DET
bracis-28373	119	11	corresponding	corresponding	ADJ
bracis-28373	119	12	curves	curve	NOUN
bracis-28373	119	13	.	.	PUNCT
bracis-28373	120	1	(	(	PUNCT
bracis-28373	120	2	color	color	NOUN
bracis-28373	120	3	figure	figure	NOUN
bracis-28373	120	4	online	online	ADV
bracis-28373	120	5	)	)	PUNCT
bracis-28373	120	6	full	full	ADJ
bracis-28373	120	7	size	size	NOUN
bracis-28373	120	8	image	image	NOUN
bracis-28373	120	9	3.3	3.3	NUM
bracis-28373	120	10	occam	occam	PROPN
bracis-28373	120	11	razor	razor	PROPN
bracis-28373	120	12	and	and	CCONJ
bracis-28373	120	13	 	 	SPACE
bracis-28373	120	14	marginal	marginal	ADJ
bracis-28373	120	15	likehood	likehood	NOUN
bracis-28373	120	16	the	the	DET
bracis-28373	120	17	marginal	marginal	ADJ
bracis-28373	120	18	likelihood	likelihood	NOUN
bracis-28373	120	19	automatically	automatically	ADV
bracis-28373	120	20	encapsulates	encapsulate	VERB
bracis-28373	120	21	a	a	DET
bracis-28373	120	22	notion	notion	NOUN
bracis-28373	120	23	of	of	ADP
bracis-28373	120	24	occam	occam	PROPN
bracis-28373	120	25	’s	’s	PART
bracis-28373	120	26	razor	razor	NOUN
bracis-28373	120	27	.	.	PUNCT
bracis-28373	121	1	to	to	PART
bracis-28373	121	2	illustrate	illustrate	VERB
bracis-28373	121	3	this	this	PRON
bracis-28373	121	4	,	,	PUNCT
bracis-28373	121	5	we	we	PRON
bracis-28373	121	6	estimate	estimate	VERB
bracis-28373	121	7	laplace	laplace	NOUN
bracis-28373	121	8	approximation	approximation	NOUN
bracis-28373	121	9	to	to	PART
bracis-28373	121	10	find	find	VERB
bracis-28373	121	11	a	a	DET
bracis-28373	121	12	gaussian	gaussian	ADJ
bracis-28373	121	13	approximation	approximation	NOUN
bracis-28373	121	14	to	to	ADP
bracis-28373	121	15	a	a	DET
bracis-28373	121	16	probability	probability	NOUN
bracis-28373	121	17	density	density	NOUN
bracis-28373	121	18	defined	define	VERB
bracis-28373	121	19	over	over	ADP
bracis-28373	121	20	a	a	DET
bracis-28373	121	21	set	set	NOUN
bracis-28373	121	22	of	of	ADP
bracis-28373	121	23	continuous	continuous	ADJ
bracis-28373	121	24	variables	variable	NOUN
bracis-28373	121	25	.	.	PUNCT
bracis-28373	122	1	we	we	PRON
bracis-28373	122	2	can	can	AUX
bracis-28373	122	3	see	see	VERB
bracis-28373	122	4	a	a	DET
bracis-28373	122	5	toy	toy	NOUN
bracis-28373	122	6	example	example	NOUN
bracis-28373	122	7	for	for	ADP
bracis-28373	122	8	laplace	laplace	NOUN
bracis-28373	122	9	approximation	approximation	NOUN
bracis-28373	122	10	in	in	ADP
bracis-28373	122	11	fig	fig	NOUN
bracis-28373	122	12	.	.	PUNCT
bracis-28373	122	13	 	 	SPACE
bracis-28373	123	1	2	2	NUM
bracis-28373	123	2	.	.	X
bracis-28373	123	3	figure	figure	NOUN
bracis-28373	123	4	 	 	SPACE
bracis-28373	123	5	2	2	NUM
bracis-28373	123	6	(	(	PUNCT
bracis-28373	123	7	a	a	NOUN
bracis-28373	123	8	)	)	PUNCT
bracis-28373	123	9	,	,	PUNCT
bracis-28373	123	10	the	the	DET
bracis-28373	123	11	normalized	normalize	VERB
bracis-28373	123	12	distribution	distribution	NOUN
bracis-28373	123	13	p(z	p(z	NOUN
bracis-28373	123	14	)	)	PUNCT
bracis-28373	123	15	is	be	AUX
bracis-28373	123	16	shown	show	VERB
bracis-28373	123	17	alongside	alongside	ADP
bracis-28373	123	18	the	the	DET
bracis-28373	123	19	laplace	laplace	NOUN
bracis-28373	123	20	approximation	approximation	NOUN
bracis-28373	123	21	centered	center	VERB
bracis-28373	123	22	on	on	ADP
bracis-28373	123	23	the	the	DET
bracis-28373	123	24	mode	mode	NOUN
bracis-28373	123	25	\(z_0\	\(z_0\	PROPN
bracis-28373	123	26	)	)	PUNCT
bracis-28373	123	27	of	of	ADP
bracis-28373	123	28	p(z	p(z	NOUN
bracis-28373	123	29	)	)	PUNCT
bracis-28373	123	30	.	.	PUNCT
bracis-28373	124	1	the	the	DET
bracis-28373	124	2	laplace	laplace	NOUN
bracis-28373	124	3	approximation	approximation	NOUN
bracis-28373	124	4	,	,	PUNCT
bracis-28373	124	5	depicted	depict	VERB
bracis-28373	124	6	by	by	ADP
bracis-28373	124	7	the	the	DET
bracis-28373	124	8	orange	orange	PROPN
bracis-28373	124	9	curve	curve	NOUN
bracis-28373	124	10	,	,	PUNCT
bracis-28373	124	11	is	be	AUX
bracis-28373	124	12	a	a	DET
bracis-28373	124	13	gaussian	gaussian	ADJ
bracis-28373	124	14	distribution	distribution	NOUN
bracis-28373	124	15	that	that	PRON
bracis-28373	124	16	closely	closely	ADV
bracis-28373	124	17	matches	match	VERB
bracis-28373	124	18	the	the	DET
bracis-28373	124	19	original	original	ADJ
bracis-28373	124	20	distribution	distribution	NOUN
bracis-28373	124	21	near	near	ADP
bracis-28373	124	22	the	the	DET
bracis-28373	124	23	mode	mode	NOUN
bracis-28373	124	24	\(z_0\	\(z_0\	PROPN
bracis-28373	124	25	)	)	PUNCT
bracis-28373	124	26	.	.	PUNCT
bracis-28373	125	1	this	this	DET
bracis-28373	125	2	approximation	approximation	NOUN
bracis-28373	125	3	is	be	AUX
bracis-28373	125	4	commonly	commonly	ADV
bracis-28373	125	5	employed	employ	VERB
bracis-28373	125	6	to	to	PART
bracis-28373	125	7	simplify	simplify	VERB
bracis-28373	125	8	calculations	calculation	NOUN
bracis-28373	125	9	and	and	CCONJ
bracis-28373	125	10	provide	provide	VERB
bracis-28373	125	11	a	a	DET
bracis-28373	125	12	more	more	ADV
bracis-28373	125	13	manageable	manageable	ADJ
bracis-28373	125	14	representation	representation	NOUN
bracis-28373	125	15	of	of	ADP
bracis-28373	125	16	complex	complex	ADJ
bracis-28373	125	17	problems	problem	NOUN
bracis-28373	125	18	.	.	PUNCT
bracis-28373	126	1	figure	figure	VERB
bracis-28373	126	2	 	 	SPACE
bracis-28373	126	3	2	2	NUM
bracis-28373	126	4	(	(	PUNCT
bracis-28373	126	5	b	b	NOUN
bracis-28373	126	6	)	)	PUNCT
bracis-28373	126	7	presents	present	VERB
bracis-28373	126	8	the	the	DET
bracis-28373	126	9	negative	negative	ADJ
bracis-28373	126	10	logarithms	logarithm	NOUN
bracis-28373	126	11	of	of	ADP
bracis-28373	126	12	the	the	DET
bracis-28373	126	13	corresponding	corresponding	ADJ
bracis-28373	126	14	curves	curve	NOUN
bracis-28373	126	15	.	.	PUNCT
bracis-28373	127	1	the	the	DET
bracis-28373	127	2	logarithmic	logarithmic	ADJ
bracis-28373	127	3	scale	scale	NOUN
bracis-28373	127	4	enhances	enhance	VERB
bracis-28373	127	5	subtle	subtle	ADJ
bracis-28373	127	6	differences	difference	NOUN
bracis-28373	127	7	between	between	ADP
bracis-28373	127	8	the	the	DET
bracis-28373	127	9	curves	curve	NOUN
bracis-28373	127	10	.	.	PUNCT
bracis-28373	128	1	notably	notably	ADV
bracis-28373	128	2	,	,	PUNCT
bracis-28373	128	3	the	the	DET
bracis-28373	128	4	laplace	laplace	NOUN
bracis-28373	128	5	approximation	approximation	NOUN
bracis-28373	128	6	(	(	PUNCT
bracis-28373	128	7	orange	orange	ADJ
bracis-28373	128	8	line	line	NOUN
bracis-28373	128	9	)	)	PUNCT
bracis-28373	128	10	exhibits	exhibit	VERB
bracis-28373	128	11	a	a	DET
bracis-28373	128	12	similar	similar	ADJ
bracis-28373	128	13	fit	fit	NOUN
bracis-28373	128	14	to	to	ADP
bracis-28373	128	15	the	the	DET
bracis-28373	128	16	original	original	ADJ
bracis-28373	128	17	curve	curve	NOUN
bracis-28373	128	18	(	(	PUNCT
bracis-28373	128	19	blue	blue	ADJ
bracis-28373	128	20	line	line	NOUN
bracis-28373	128	21	)	)	PUNCT
bracis-28373	128	22	near	near	ADP
bracis-28373	128	23	the	the	DET
bracis-28373	128	24	mode	mode	NOUN
bracis-28373	128	25	\(z_0\	\(z_0\	PROPN
bracis-28373	128	26	)	)	PUNCT
bracis-28373	128	27	.	.	PUNCT
bracis-28373	129	1	this	this	DET
bracis-28373	129	2	figure	figure	NOUN
bracis-28373	129	3	effectively	effectively	ADV
bracis-28373	129	4	showcases	showcase	VERB
bracis-28373	129	5	the	the	DET
bracis-28373	129	6	application	application	NOUN
bracis-28373	129	7	of	of	ADP
bracis-28373	129	8	laplace	laplace	NOUN
bracis-28373	129	9	approximation	approximation	NOUN
bracis-28373	129	10	for	for	ADP
bracis-28373	129	11	estimating	estimate	VERB
bracis-28373	129	12	a	a	DET
bracis-28373	129	13	gaussian	gaussian	ADJ
bracis-28373	129	14	distribution	distribution	NOUN
bracis-28373	129	15	that	that	PRON
bracis-28373	129	16	effectively	effectively	ADV
bracis-28373	129	17	approximates	approximate	VERB
bracis-28373	129	18	a	a	DET
bracis-28373	129	19	complex	complex	ADJ
bracis-28373	129	20	probability	probability	NOUN
bracis-28373	129	21	distribution	distribution	NOUN
bracis-28373	129	22	.	.	PUNCT
bracis-28373	130	1	we	we	PRON
bracis-28373	130	2	can	can	AUX
bracis-28373	130	3	consider	consider	VERB
bracis-28373	130	4	the	the	DET
bracis-28373	130	5	log	log	NOUN
bracis-28373	130	6	of	of	ADP
bracis-28373	130	7	the	the	DET
bracis-28373	130	8	laplace	laplace	NOUN
bracis-28373	130	9	marginal	marginal	ADJ
bracis-28373	130	10	likelihood	likelihood	NOUN
bracis-28373	130	11	(	(	PUNCT
bracis-28373	130	12	lml	lml	NOUN
bracis-28373	130	13	)	)	PUNCT
bracis-28373	130	14	in	in	ADP
bracis-28373	130	15	eq	eq	ADP
bracis-28373	130	16	.	.	PUNCT
bracis-28373	130	17	 	 	SPACE
bracis-28373	130	18	2	2	NUM
bracis-28373	130	19	as	as	ADP
bracis-28373	130	20	$	$	SYM
bracis-28373	130	21	$	$	SYM
bracis-28373	130	22	\begin{aligned	\begin{aligne	VERB
bracis-28373	130	23	}	}	PUNCT
bracis-28373	130	24	\log	\log	PROPN
bracis-28373	130	25	p(\mathcal	p(\mathcal	ADP
bracis-28373	130	26	{	{	PUNCT
bracis-28373	130	27	d	d	NOUN
bracis-28373	130	28	}	}	PUNCT
bracis-28373	130	29	)	)	PUNCT
bracis-28373	131	1	\propto	\propto	ADP
bracis-28373	131	2	\log	\log	PROPN
bracis-28373	131	3	p(\mathcal	p(\mathcal	ADP
bracis-28373	131	4	{	{	PUNCT
bracis-28373	131	5	d	d	NOUN
bracis-28373	131	6	}	}	PUNCT
bracis-28373	131	7	,	,	PUNCT
bracis-28373	131	8	{	{	PUNCT
bracis-28373	131	9	\textbf	\textbf	PROPN
bracis-28373	131	10	{	{	PUNCT
bracis-28373	131	11	w}}_{\text	w}}_{\text	X
bracis-28373	131	12	{	{	PUNCT
bracis-28373	131	13	map	map	NOUN
bracis-28373	131	14	}	}	PUNCT
bracis-28373	131	15	}	}	PUNCT
bracis-28373	131	16	)	)	PUNCT
bracis-28373	131	17	+	+	CCONJ
bracis-28373	131	18	\underbrace{\frac{m}{2	\underbrace{\frac{m}{2	ADJ
bracis-28373	131	19	}	}	PUNCT
bracis-28373	131	20	\log	\log	PROPN
bracis-28373	131	21	(	(	PUNCT
bracis-28373	131	22	2\pi	2\pi	PROPN
bracis-28373	131	23	)	)	PUNCT
bracis-28373	131	24	\frac{1}{2	\frac{1}{2	VERB
bracis-28373	131	25	}	}	PUNCT
bracis-28373	131	26	\log	\log	PROPN
bracis-28373	131	27	|{\textbf	|{\textbf	NOUN
bracis-28373	131	28	{	{	PUNCT
bracis-28373	131	29	h}}_{map}|}_\text	h}}_{map}|}_\text	PROPN
bracis-28373	131	30	{	{	PUNCT
bracis-28373	131	31	occam	occam	PROPN
bracis-28373	131	32	factor	factor	NOUN
bracis-28373	131	33	}	}	PUNCT
bracis-28373	131	34	.	.	PUNCT
bracis-28373	132	1	\end{aligned}$$	\end{aligned}$$	PROPN
bracis-28373	132	2	(	(	PUNCT
bracis-28373	132	3	3	3	X
bracis-28373	132	4	)	)	PUNCT
bracis-28373	132	5	the	the	DET
bracis-28373	132	6	relationship	relationship	NOUN
bracis-28373	132	7	between	between	ADP
bracis-28373	132	8	occam	occam	PROPN
bracis-28373	132	9	’s	’s	PART
bracis-28373	132	10	razor	razor	PROPN
bracis-28373	132	11	and	and	CCONJ
bracis-28373	132	12	laplace	laplace	NOUN
bracis-28373	132	13	approximation	approximation	NOUN
bracis-28373	132	14	is	be	AUX
bracis-28373	132	15	deeply	deeply	ADV
bracis-28373	132	16	rooted	rooted	ADJ
bracis-28373	132	17	in	in	ADP
bracis-28373	132	18	the	the	DET
bracis-28373	132	19	theory	theory	NOUN
bracis-28373	132	20	of	of	ADP
bracis-28373	132	21	bayesian	bayesian	NOUN
bracis-28373	132	22	inference	inference	NOUN
bracis-28373	132	23	.	.	PUNCT
bracis-28373	133	1	laplace	laplace	PROPN
bracis-28373	133	2	approximation	approximation	NOUN
bracis-28373	133	3	is	be	AUX
bracis-28373	133	4	a	a	DET
bracis-28373	133	5	technique	technique	NOUN
bracis-28373	133	6	that	that	PRON
bracis-28373	133	7	allows	allow	VERB
bracis-28373	133	8	us	we	PRON
bracis-28373	133	9	to	to	PART
bracis-28373	133	10	approximate	approximate	VERB
bracis-28373	133	11	a	a	DET
bracis-28373	133	12	probability	probability	NOUN
bracis-28373	133	13	distribution	distribution	NOUN
bracis-28373	133	14	with	with	ADP
bracis-28373	133	15	a	a	DET
bracis-28373	133	16	gaussian	gaussian	ADJ
bracis-28373	133	17	distribution	distribution	NOUN
bracis-28373	133	18	around	around	ADP
bracis-28373	133	19	the	the	DET
bracis-28373	133	20	maximum	maximum	NOUN
bracis-28373	133	21	a	a	DET
bracis-28373	133	22	posteriori	posteriori	NOUN
bracis-28373	133	23	point	point	NOUN
bracis-28373	133	24	.	.	PUNCT
bracis-28373	134	1	the	the	DET
bracis-28373	134	2	maximum	maximum	NOUN
bracis-28373	134	3	a	a	DET
bracis-28373	134	4	posteriori	posteriori	NOUN
bracis-28373	134	5	point	point	NOUN
bracis-28373	134	6	is	be	AUX
bracis-28373	134	7	often	often	ADV
bracis-28373	134	8	interpreted	interpret	VERB
bracis-28373	134	9	as	as	ADP
bracis-28373	134	10	the	the	DET
bracis-28373	134	11	most	most	ADV
bracis-28373	134	12	likely	likely	ADJ
bracis-28373	134	13	solution	solution	NOUN
bracis-28373	134	14	to	to	ADP
bracis-28373	134	15	a	a	DET
bracis-28373	134	16	given	give	VERB
bracis-28373	134	17	modeling	modeling	NOUN
bracis-28373	134	18	problem	problem	NOUN
bracis-28373	134	19	.	.	PUNCT
bracis-28373	135	1	occam	occam	PROPN
bracis-28373	135	2	’s	’s	PART
bracis-28373	135	3	razor	razor	NOUN
bracis-28373	135	4	,	,	PUNCT
bracis-28373	135	5	on	on	ADP
bracis-28373	135	6	the	the	DET
bracis-28373	135	7	other	other	ADJ
bracis-28373	135	8	hand	hand	NOUN
bracis-28373	135	9	,	,	PUNCT
bracis-28373	135	10	is	be	AUX
bracis-28373	135	11	a	a	DET
bracis-28373	135	12	philosophical	philosophical	ADJ
bracis-28373	135	13	principle	principle	NOUN
bracis-28373	135	14	that	that	PRON
bracis-28373	135	15	states	state	VERB
bracis-28373	135	16	that	that	SCONJ
bracis-28373	135	17	if	if	SCONJ
bracis-28373	135	18	there	there	PRON
bracis-28373	135	19	are	be	VERB
bracis-28373	135	20	several	several	ADJ
bracis-28373	135	21	possible	possible	ADJ
bracis-28373	135	22	explanations	explanation	NOUN
bracis-28373	135	23	for	for	ADP
bracis-28373	135	24	a	a	DET
bracis-28373	135	25	given	give	VERB
bracis-28373	135	26	set	set	NOUN
bracis-28373	135	27	of	of	ADP
bracis-28373	135	28	observations	observation	NOUN
bracis-28373	135	29	,	,	PUNCT
bracis-28373	135	30	the	the	DET
bracis-28373	135	31	simplest	simple	ADJ
bracis-28373	135	32	explanation	explanation	NOUN
bracis-28373	135	33	is	be	AUX
bracis-28373	135	34	the	the	DET
bracis-28373	135	35	most	most	ADV
bracis-28373	135	36	likely	likely	ADJ
bracis-28373	135	37	.	.	PUNCT
bracis-28373	136	1	in	in	ADP
bracis-28373	136	2	bayesian	bayesian	NOUN
bracis-28373	136	3	inference	inference	NOUN
bracis-28373	136	4	theory	theory	NOUN
bracis-28373	136	5	,	,	PUNCT
bracis-28373	136	6	this	this	PRON
bracis-28373	136	7	translates	translate	VERB
bracis-28373	136	8	into	into	ADP
bracis-28373	136	9	the	the	DET
bracis-28373	136	10	fact	fact	NOUN
bracis-28373	136	11	that	that	SCONJ
bracis-28373	136	12	when	when	SCONJ
bracis-28373	136	13	making	make	VERB
bracis-28373	136	14	inferences	inference	NOUN
bracis-28373	136	15	about	about	ADP
bracis-28373	136	16	a	a	DET
bracis-28373	136	17	model	model	NOUN
bracis-28373	136	18	,	,	PUNCT
bracis-28373	136	19	we	we	PRON
bracis-28373	136	20	should	should	AUX
bracis-28373	136	21	prefer	prefer	VERB
bracis-28373	136	22	simpler	simple	ADJ
bracis-28373	136	23	and	and	CCONJ
bracis-28373	136	24	less	less	ADV
bracis-28373	136	25	complex	complex	ADJ
bracis-28373	136	26	models	model	NOUN
bracis-28373	136	27	unless	unless	SCONJ
bracis-28373	136	28	there	there	PRON
bracis-28373	136	29	is	be	VERB
bracis-28373	136	30	clear	clear	ADJ
bracis-28373	136	31	evidence	evidence	NOUN
bracis-28373	136	32	on	on	ADP
bracis-28373	136	33	the	the	DET
bracis-28373	136	34	contrary	contrary	NOUN
bracis-28373	136	35	.	.	PUNCT
bracis-28373	137	1	when	when	SCONJ
bracis-28373	137	2	we	we	PRON
bracis-28373	137	3	consider	consider	VERB
bracis-28373	137	4	eq	eq	ADP
bracis-28373	137	5	.	.	PUNCT
bracis-28373	137	6	 	 	SPACE
bracis-28373	137	7	3	3	NUM
bracis-28373	137	8	as	as	ADP
bracis-28373	137	9	our	our	PRON
bracis-28373	137	10	loss	loss	NOUN
bracis-28373	137	11	function	function	NOUN
bracis-28373	137	12	for	for	ADP
bracis-28373	137	13	training	train	VERB
bracis-28373	137	14	the	the	DET
bracis-28373	137	15	neural	neural	ADJ
bracis-28373	137	16	network	network	NOUN
bracis-28373	137	17	,	,	PUNCT
bracis-28373	137	18	we	we	PRON
bracis-28373	137	19	realize	realize	VERB
bracis-28373	137	20	that	that	SCONJ
bracis-28373	137	21	maximizing	maximize	VERB
bracis-28373	137	22	the	the	DET
bracis-28373	137	23	fit	fit	NOUN
bracis-28373	137	24	of	of	ADP
bracis-28373	137	25	the	the	DET
bracis-28373	137	26	model	model	NOUN
bracis-28373	137	27	’s	’s	PART
bracis-28373	137	28	marginal	marginal	ADJ
bracis-28373	137	29	likelihood	likelihood	NOUN
bracis-28373	137	30	corresponds	correspond	VERB
bracis-28373	137	31	to	to	ADP
bracis-28373	137	32	increasing	increase	VERB
bracis-28373	137	33	the	the	DET
bracis-28373	137	34	value	value	NOUN
bracis-28373	137	35	\(\log	\(\log	NOUN
bracis-28373	137	36	p(\mathcal	p(\mathcal	ADP
bracis-28373	137	37	{	{	PUNCT
bracis-28373	137	38	d	d	NOUN
bracis-28373	137	39	}	}	PUNCT
bracis-28373	137	40	,	,	PUNCT
bracis-28373	137	41	{	{	PUNCT
bracis-28373	137	42	\textbf	\textbf	PROPN
bracis-28373	137	43	{	{	PUNCT
bracis-28373	137	44	w}}_{\text	w}}_{\text	X
bracis-28373	137	45	{	{	PUNCT
bracis-28373	137	46	map}})\	map}})\	NOUN
bracis-28373	137	47	)	)	PUNCT
bracis-28373	137	48	and	and	CCONJ
bracis-28373	137	49	minimizing	minimize	VERB
bracis-28373	137	50	the	the	DET
bracis-28373	137	51	complexity	complexity	NOUN
bracis-28373	137	52	term	term	NOUN
bracis-28373	137	53	\(\log	\(\log	NOUN
bracis-28373	137	54	|{\textbf	|{\textbf	PROPN
bracis-28373	137	55	{	{	PUNCT
bracis-28373	137	56	h}}_{map}|\	h}}_{map}|\	ADJ
bracis-28373	137	57	)	)	PUNCT
bracis-28373	137	58	.	.	PUNCT
bracis-28373	138	1	the	the	DET
bracis-28373	138	2	complexity	complexity	NOUN
bracis-28373	138	3	term	term	NOUN
bracis-28373	138	4	depends	depend	VERB
bracis-28373	138	5	on	on	ADP
bracis-28373	138	6	the	the	DET
bracis-28373	138	7	log	log	NOUN
bracis-28373	138	8	determinant	determinant	ADJ
bracis-28373	138	9	of	of	ADP
bracis-28373	138	10	the	the	DET
bracis-28373	138	11	laplace	laplace	NOUN
bracis-28373	138	12	posterior	posterior	ADJ
bracis-28373	138	13	covariance	covariance	NOUN
bracis-28373	138	14	.	.	PUNCT
bracis-28373	139	1	therefore	therefore	ADV
bracis-28373	139	2	,	,	PUNCT
bracis-28373	139	3	if	if	SCONJ
bracis-28373	139	4	\(\log	\(\log	NOUN
bracis-28373	139	5	|{\textbf	|{\textbf	NOUN
bracis-28373	139	6	{	{	PUNCT
bracis-28373	139	7	h}}_{map}|\	h}}_{map}|\	ADJ
bracis-28373	139	8	)	)	PUNCT
bracis-28373	139	9	is	be	AUX
bracis-28373	139	10	large	large	ADJ
bracis-28373	139	11	,	,	PUNCT
bracis-28373	139	12	the	the	DET
bracis-28373	139	13	model	model	NOUN
bracis-28373	139	14	strongly	strongly	ADV
bracis-28373	139	15	correlates	correlate	VERB
bracis-28373	139	16	with	with	ADP
bracis-28373	139	17	the	the	DET
bracis-28373	139	18	training	training	NOUN
bracis-28373	139	19	data	datum	NOUN
bracis-28373	139	20	 	 	SPACE
bracis-28373	139	21	[	[	X
bracis-28373	139	22	11	11	NUM
bracis-28373	139	23	]	]	PUNCT
bracis-28373	139	24	.	.	PUNCT
bracis-28373	140	1	so	so	ADV
bracis-28373	140	2	,	,	PUNCT
bracis-28373	140	3	maximizing	maximize	VERB
bracis-28373	140	4	the	the	DET
bracis-28373	140	5	laplace	laplace	NOUN
bracis-28373	140	6	\(\log	\(\log	NOUN
bracis-28373	140	7	p(\mathcal	p(\mathcal	ADP
bracis-28373	140	8	{	{	PUNCT
bracis-28373	140	9	d})\	d})\	NOUN
bracis-28373	140	10	)	)	PUNCT
bracis-28373	140	11	requires	require	VERB
bracis-28373	140	12	maximizing	maximize	VERB
bracis-28373	140	13	the	the	DET
bracis-28373	140	14	data	datum	NOUN
bracis-28373	140	15	fit	fit	ADJ
bracis-28373	140	16	while	while	SCONJ
bracis-28373	140	17	minimizing	minimize	VERB
bracis-28373	140	18	the	the	DET
bracis-28373	140	19	training	training	NOUN
bracis-28373	140	20	sample	sample	NOUN
bracis-28373	140	21	correlation	correlation	NOUN
bracis-28373	140	22	.	.	PUNCT
bracis-28373	141	1	the	the	DET
bracis-28373	141	2	laplace	laplace	PROPN
bracis-28373	141	3	approximation	approximation	NOUN
bracis-28373	141	4	implements	implement	NOUN
bracis-28373	141	5	occam	occam	PROPN
bracis-28373	141	6	’s	’s	PART
bracis-28373	141	7	razor	razor	NOUN
bracis-28373	141	8	as	as	SCONJ
bracis-28373	141	9	we	we	PRON
bracis-28373	141	10	make	make	VERB
bracis-28373	141	11	the	the	DET
bracis-28373	141	12	simplest	simple	ADJ
bracis-28373	141	13	possible	possible	ADJ
bracis-28373	141	14	assumption	assumption	NOUN
bracis-28373	141	15	about	about	ADP
bracis-28373	141	16	the	the	DET
bracis-28373	141	17	posterior	posterior	ADJ
bracis-28373	141	18	distribution	distribution	NOUN
bracis-28373	141	19	.	.	PUNCT
bracis-28373	142	1	furthermore	furthermore	ADV
bracis-28373	142	2	,	,	PUNCT
bracis-28373	142	3	the	the	DET
bracis-28373	142	4	laplace	laplace	NOUN
bracis-28373	142	5	approximation	approximation	NOUN
bracis-28373	142	6	has	have	AUX
bracis-28373	142	7	been	be	AUX
bracis-28373	142	8	used	use	VERB
bracis-28373	142	9	in	in	ADP
bracis-28373	142	10	many	many	ADJ
bracis-28373	142	11	applications	application	NOUN
bracis-28373	142	12	,	,	PUNCT
bracis-28373	142	13	including	include	VERB
bracis-28373	142	14	training	train	VERB
bracis-28373	142	15	machine	machine	NOUN
bracis-28373	142	16	learning	learning	NOUN
bracis-28373	142	17	models	model	NOUN
bracis-28373	142	18	in	in	ADP
bracis-28373	142	19	federated	federated	ADJ
bracis-28373	142	20	environments	environment	NOUN
bracis-28373	142	21	where	where	SCONJ
bracis-28373	142	22	data	datum	NOUN
bracis-28373	142	23	privacy	privacy	NOUN
bracis-28373	142	24	is	be	AUX
bracis-28373	142	25	critical	critical	ADJ
bracis-28373	142	26	.	.	PUNCT
bracis-28373	143	1	in	in	ADP
bracis-28373	143	2	these	these	DET
bracis-28373	143	3	scenarios	scenario	NOUN
bracis-28373	143	4	,	,	PUNCT
bracis-28373	143	5	it	it	PRON
bracis-28373	143	6	is	be	AUX
bracis-28373	143	7	essential	essential	ADJ
bracis-28373	143	8	to	to	PART
bracis-28373	143	9	have	have	VERB
bracis-28373	143	10	a	a	DET
bracis-28373	143	11	model	model	NOUN
bracis-28373	143	12	that	that	PRON
bracis-28373	143	13	can	can	AUX
bracis-28373	143	14	generalize	generalize	VERB
bracis-28373	143	15	well	well	ADV
bracis-28373	143	16	from	from	ADP
bracis-28373	143	17	a	a	DET
bracis-28373	143	18	small	small	ADJ
bracis-28373	143	19	dataset	dataset	NOUN
bracis-28373	143	20	.	.	PUNCT
bracis-28373	144	1	the	the	DET
bracis-28373	144	2	laplace	laplace	NOUN
bracis-28373	144	3	approximation	approximation	NOUN
bracis-28373	144	4	can	can	AUX
bracis-28373	144	5	help	help	VERB
bracis-28373	144	6	achieve	achieve	VERB
bracis-28373	144	7	this	this	DET
bracis-28373	144	8	goal	goal	NOUN
bracis-28373	144	9	by	by	ADP
bracis-28373	144	10	providing	provide	VERB
bracis-28373	144	11	a	a	DET
bracis-28373	144	12	way	way	NOUN
bracis-28373	144	13	to	to	PART
bracis-28373	144	14	regularize	regularize	VERB
bracis-28373	144	15	the	the	DET
bracis-28373	144	16	model	model	NOUN
bracis-28373	144	17	and	and	CCONJ
bracis-28373	144	18	avoid	avoid	VERB
bracis-28373	144	19	overfitting	overfitte	VERB
bracis-28373	144	20	.	.	PUNCT
bracis-28373	145	1	3.4	3.4	NUM
bracis-28373	145	2	federated	federate	VERB
bracis-28373	145	3	learning	learn	VERB
bracis-28373	145	4	fig	fig	NOUN
bracis-28373	145	5	.	.	PUNCT
bracis-28373	146	1	3	3	X
bracis-28373	146	2	.	.	X
bracis-28373	146	3	left	leave	VERB
bracis-28373	146	4	:	:	PUNCT
bracis-28373	146	5	conventional	conventional	ADJ
bracis-28373	146	6	(	(	PUNCT
bracis-28373	146	7	client	client	NOUN
bracis-28373	146	8	-	-	PUNCT
bracis-28373	146	9	server	server	NOUN
bracis-28373	146	10	)	)	PUNCT
bracis-28373	146	11	federated	federated	ADJ
bracis-28373	146	12	learning	learning	NOUN
bracis-28373	146	13	scheme	scheme	NOUN
bracis-28373	146	14	.	.	PUNCT
bracis-28373	147	1	right	right	ADJ
bracis-28373	147	2	:	:	PUNCT
bracis-28373	147	3	training	training	NOUN
bracis-28373	147	4	of	of	ADP
bracis-28373	147	5	a	a	DET
bracis-28373	147	6	simple	simple	ADJ
bracis-28373	147	7	data	data	NOUN
bracis-28373	147	8	flow	flow	NOUN
bracis-28373	147	9	model	model	NOUN
bracis-28373	147	10	in	in	ADP
bracis-28373	147	11	federated	federated	ADJ
bracis-28373	147	12	learning	learning	NOUN
bracis-28373	147	13	.	.	PUNCT
bracis-28373	148	1	full	full	ADJ
bracis-28373	148	2	size	size	NOUN
bracis-28373	148	3	image	image	NOUN
bracis-28373	148	4	in	in	ADP
bracis-28373	148	5	federated	federated	ADJ
bracis-28373	148	6	learning	learning	NOUN
bracis-28373	148	7	,	,	PUNCT
bracis-28373	148	8	users	user	NOUN
bracis-28373	148	9	collaboratively	collaboratively	ADV
bracis-28373	148	10	train	train	VERB
bracis-28373	148	11	a	a	DET
bracis-28373	148	12	machine	machine	NOUN
bracis-28373	148	13	learning	learn	VERB
bracis-28373	148	14	model	model	NOUN
bracis-28373	148	15	without	without	ADP
bracis-28373	148	16	sharing	share	VERB
bracis-28373	148	17	their	their	PRON
bracis-28373	148	18	raw	raw	ADJ
bracis-28373	148	19	data	datum	NOUN
bracis-28373	148	20	.	.	PUNCT
bracis-28373	149	1	the	the	DET
bracis-28373	149	2	process	process	NOUN
bracis-28373	149	3	consists	consist	VERB
bracis-28373	149	4	of	of	ADP
bracis-28373	149	5	three	three	NUM
bracis-28373	149	6	main	main	ADJ
bracis-28373	149	7	steps	step	NOUN
bracis-28373	149	8	,	,	PUNCT
bracis-28373	149	9	as	as	SCONJ
bracis-28373	149	10	can	can	AUX
bracis-28373	149	11	see	see	VERB
bracis-28373	149	12	in	in	ADP
bracis-28373	149	13	fig	fig	NOUN
bracis-28373	149	14	.	.	PUNCT
bracis-28373	149	15	 	 	SPACE
bracis-28373	150	1	3	3	NUM
bracis-28373	150	2	:	:	PUNCT
bracis-28373	150	3	–	–	PUNCT
bracis-28373	150	4	(	(	PUNCT
bracis-28373	150	5	step	step	NOUN
bracis-28373	150	6	1	1	NUM
bracis-28373	150	7	)	)	PUNCT
bracis-28373	150	8	task	task	NOUN
bracis-28373	150	9	initialization	initialization	NOUN
bracis-28373	150	10	:	:	PUNCT
bracis-28373	150	11	the	the	DET
bracis-28373	150	12	system	system	NOUN
bracis-28373	150	13	initializes	initialize	VERB
bracis-28373	150	14	the	the	DET
bracis-28373	150	15	local	local	ADJ
bracis-28373	150	16	models	model	NOUN
bracis-28373	150	17	and	and	CCONJ
bracis-28373	150	18	necessary	necessary	ADJ
bracis-28373	150	19	hyperparameters	hyperparameter	NOUN
bracis-28373	150	20	for	for	ADP
bracis-28373	150	21	the	the	DET
bracis-28373	150	22	learning	learning	NOUN
bracis-28373	150	23	task	task	NOUN
bracis-28373	150	24	.	.	PUNCT
bracis-28373	151	1	each	each	DET
bracis-28373	151	2	user	user	NOUN
bracis-28373	151	3	prepares	prepare	VERB
bracis-28373	151	4	their	their	PRON
bracis-28373	151	5	local	local	ADJ
bracis-28373	151	6	model	model	NOUN
bracis-28373	151	7	using	use	VERB
bracis-28373	151	8	their	their	PRON
bracis-28373	151	9	respective	respective	ADJ
bracis-28373	151	10	dataset	dataset	NOUN
bracis-28373	151	11	.	.	PUNCT
bracis-28373	152	1	–	–	PUNCT
bracis-28373	152	2	(	(	PUNCT
bracis-28373	152	3	step	step	NOUN
bracis-28373	152	4	2	2	NUM
bracis-28373	152	5	)	)	PUNCT
bracis-28373	152	6	local	local	ADJ
bracis-28373	152	7	model	model	NOUN
bracis-28373	152	8	training	training	NOUN
bracis-28373	152	9	and	and	CCONJ
bracis-28373	152	10	update	update	NOUN
bracis-28373	152	11	:	:	PUNCT
bracis-28373	152	12	each	each	DET
bracis-28373	152	13	user	user	NOUN
bracis-28373	152	14	independently	independently	ADV
bracis-28373	152	15	trains	train	VERB
bracis-28373	152	16	their	their	PRON
bracis-28373	152	17	local	local	ADJ
bracis-28373	152	18	model	model	NOUN
bracis-28373	152	19	using	use	VERB
bracis-28373	152	20	their	their	PRON
bracis-28373	152	21	local	local	ADJ
bracis-28373	152	22	data	datum	NOUN
bracis-28373	152	23	.	.	PUNCT
bracis-28373	153	1	the	the	DET
bracis-28373	153	2	goal	goal	NOUN
bracis-28373	153	3	is	be	AUX
bracis-28373	153	4	to	to	PART
bracis-28373	153	5	find	find	VERB
bracis-28373	153	6	the	the	DET
bracis-28373	153	7	optimal	optimal	ADJ
bracis-28373	153	8	parameters	parameter	NOUN
bracis-28373	153	9	that	that	PRON
bracis-28373	153	10	minimize	minimize	VERB
bracis-28373	153	11	the	the	DET
bracis-28373	153	12	loss	loss	NOUN
bracis-28373	153	13	function	function	NOUN
bracis-28373	153	14	specific	specific	ADJ
bracis-28373	153	15	to	to	ADP
bracis-28373	153	16	their	their	PRON
bracis-28373	153	17	dataset	dataset	NOUN
bracis-28373	153	18	.	.	PUNCT
bracis-28373	154	1	this	this	DET
bracis-28373	154	2	step	step	NOUN
bracis-28373	154	3	ensures	ensure	VERB
bracis-28373	154	4	that	that	SCONJ
bracis-28373	154	5	each	each	DET
bracis-28373	154	6	user	user	NOUN
bracis-28373	154	7	’s	’s	PART
bracis-28373	154	8	model	model	NOUN
bracis-28373	154	9	is	be	AUX
bracis-28373	154	10	tailored	tailor	VERB
bracis-28373	154	11	to	to	ADP
bracis-28373	154	12	their	their	PRON
bracis-28373	154	13	data	datum	NOUN
bracis-28373	154	14	and	and	CCONJ
bracis-28373	154	15	captures	capture	VERB
bracis-28373	154	16	their	their	PRON
bracis-28373	154	17	local	local	ADJ
bracis-28373	154	18	patterns	pattern	NOUN
bracis-28373	154	19	.	.	PUNCT
bracis-28373	155	1	–	–	PUNCT
bracis-28373	155	2	(	(	PUNCT
bracis-28373	155	3	step	step	NOUN
bracis-28373	155	4	3	3	NUM
bracis-28373	155	5	)	)	PUNCT
bracis-28373	155	6	model	model	NOUN
bracis-28373	155	7	aggregation	aggregation	NOUN
bracis-28373	155	8	and	and	CCONJ
bracis-28373	155	9	update	update	NOUN
bracis-28373	155	10	:	:	PUNCT
bracis-28373	155	11	the	the	DET
bracis-28373	155	12	server	server	NOUN
bracis-28373	155	13	aggregates	aggregate	VERB
bracis-28373	155	14	the	the	DET
bracis-28373	155	15	local	local	ADJ
bracis-28373	155	16	models	model	NOUN
bracis-28373	155	17	from	from	ADP
bracis-28373	155	18	selected	select	VERB
bracis-28373	155	19	participants	participant	NOUN
bracis-28373	155	20	and	and	CCONJ
bracis-28373	155	21	generates	generate	VERB
bracis-28373	155	22	an	an	DET
bracis-28373	155	23	updated	update	VERB
bracis-28373	155	24	global	global	ADJ
bracis-28373	155	25	model	model	NOUN
bracis-28373	155	26	,	,	PUNCT
bracis-28373	155	27	often	often	ADV
bracis-28373	155	28	referred	refer	VERB
bracis-28373	155	29	to	to	ADP
bracis-28373	155	30	as	as	ADP
bracis-28373	155	31	the	the	DET
bracis-28373	155	32	federated	federated	ADJ
bracis-28373	155	33	model	model	NOUN
bracis-28373	155	34	.	.	PUNCT
bracis-28373	156	1	the	the	DET
bracis-28373	156	2	aggregation	aggregation	NOUN
bracis-28373	156	3	process	process	NOUN
bracis-28373	156	4	typically	typically	ADV
bracis-28373	156	5	involves	involve	VERB
bracis-28373	156	6	combining	combine	VERB
bracis-28373	156	7	the	the	DET
bracis-28373	156	8	model	model	NOUN
bracis-28373	156	9	parameters	parameter	NOUN
bracis-28373	156	10	of	of	ADP
bracis-28373	156	11	the	the	DET
bracis-28373	156	12	local	local	ADJ
bracis-28373	156	13	models	model	NOUN
bracis-28373	156	14	.	.	PUNCT
bracis-28373	157	1	the	the	DET
bracis-28373	157	2	global	global	ADJ
bracis-28373	157	3	model	model	NOUN
bracis-28373	157	4	is	be	AUX
bracis-28373	157	5	then	then	ADV
bracis-28373	157	6	sent	send	VERB
bracis-28373	157	7	back	back	ADV
bracis-28373	157	8	to	to	ADP
bracis-28373	157	9	the	the	DET
bracis-28373	157	10	users	user	NOUN
bracis-28373	157	11	for	for	ADP
bracis-28373	157	12	further	further	ADJ
bracis-28373	157	13	iterations	iteration	NOUN
bracis-28373	157	14	.	.	PUNCT
bracis-28373	158	1	steps	step	NOUN
bracis-28373	158	2	2	2	NUM
bracis-28373	158	3	and	and	CCONJ
bracis-28373	158	4	3	3	NUM
bracis-28373	158	5	are	be	AUX
bracis-28373	158	6	repeated	repeat	VERB
bracis-28373	158	7	iteratively	iteratively	ADV
bracis-28373	158	8	until	until	ADP
bracis-28373	158	9	the	the	DET
bracis-28373	158	10	aggregate	aggregate	ADJ
bracis-28373	158	11	loss	loss	NOUN
bracis-28373	158	12	function	function	NOUN
bracis-28373	158	13	converges	converge	VERB
bracis-28373	158	14	or	or	CCONJ
bracis-28373	158	15	reaches	reach	VERB
bracis-28373	158	16	a	a	DET
bracis-28373	158	17	desired	desire	VERB
bracis-28373	158	18	training	training	NOUN
bracis-28373	158	19	metric	metric	NOUN
bracis-28373	158	20	.	.	PUNCT
bracis-28373	159	1	the	the	DET
bracis-28373	159	2	iterative	iterative	ADJ
bracis-28373	159	3	nature	nature	NOUN
bracis-28373	159	4	of	of	ADP
bracis-28373	159	5	the	the	DET
bracis-28373	159	6	process	process	NOUN
bracis-28373	159	7	allows	allow	VERB
bracis-28373	159	8	the	the	DET
bracis-28373	159	9	global	global	ADJ
bracis-28373	159	10	model	model	NOUN
bracis-28373	159	11	to	to	PART
bracis-28373	159	12	improve	improve	VERB
bracis-28373	159	13	over	over	ADP
bracis-28373	159	14	time	time	NOUN
bracis-28373	159	15	by	by	ADP
bracis-28373	159	16	leveraging	leverage	VERB
bracis-28373	159	17	the	the	DET
bracis-28373	159	18	collective	collective	ADJ
bracis-28373	159	19	knowledge	knowledge	NOUN
bracis-28373	159	20	from	from	ADP
bracis-28373	159	21	all	all	DET
bracis-28373	159	22	participating	participate	VERB
bracis-28373	159	23	users	user	NOUN
bracis-28373	159	24	while	while	SCONJ
bracis-28373	159	25	maintaining	maintain	VERB
bracis-28373	159	26	data	data	NOUN
bracis-28373	159	27	privacy	privacy	NOUN
bracis-28373	159	28	.	.	PUNCT
bracis-28373	160	1	3.5	3.5	NUM
bracis-28373	160	2	model	model	NOUN
bracis-28373	160	3	attack	attack	NOUN
bracis-28373	160	4	federated	federated	ADJ
bracis-28373	160	5	learning	learning	NOUN
bracis-28373	160	6	,	,	PUNCT
bracis-28373	160	7	a	a	DET
bracis-28373	160	8	distributed	distribute	VERB
bracis-28373	160	9	learning	learning	NOUN
bracis-28373	160	10	paradigm	paradigm	NOUN
bracis-28373	160	11	,	,	PUNCT
bracis-28373	160	12	allows	allow	VERB
bracis-28373	160	13	multiple	multiple	ADJ
bracis-28373	160	14	clients	client	NOUN
bracis-28373	160	15	to	to	PART
bracis-28373	160	16	collaboratively	collaboratively	ADV
bracis-28373	160	17	train	train	VERB
bracis-28373	160	18	a	a	DET
bracis-28373	160	19	global	global	ADJ
bracis-28373	160	20	model	model	NOUN
bracis-28373	160	21	without	without	ADP
bracis-28373	160	22	sharing	share	VERB
bracis-28373	160	23	their	their	PRON
bracis-28373	160	24	raw	raw	ADJ
bracis-28373	160	25	data	datum	NOUN
bracis-28373	160	26	.	.	PUNCT
bracis-28373	161	1	however	however	ADV
bracis-28373	161	2	,	,	PUNCT
bracis-28373	161	3	this	this	DET
bracis-28373	161	4	collaborative	collaborative	ADJ
bracis-28373	161	5	nature	nature	NOUN
bracis-28373	161	6	makes	make	VERB
bracis-28373	161	7	federated	federated	ADJ
bracis-28373	161	8	learning	learning	NOUN
bracis-28373	161	9	vulnerable	vulnerable	ADJ
bracis-28373	161	10	to	to	ADP
bracis-28373	161	11	malicious	malicious	ADJ
bracis-28373	161	12	attacks	attack	NOUN
bracis-28373	161	13	.	.	PUNCT
bracis-28373	162	1	before	before	ADP
bracis-28373	162	2	launching	launch	VERB
bracis-28373	162	3	our	our	PRON
bracis-28373	162	4	attack	attack	NOUN
bracis-28373	162	5	on	on	ADP
bracis-28373	162	6	federated	federated	ADJ
bracis-28373	162	7	learning	learning	NOUN
bracis-28373	162	8	,	,	PUNCT
bracis-28373	162	9	an	an	DET
bracis-28373	162	10	attacker	attacker	NOUN
bracis-28373	162	11	must	must	AUX
bracis-28373	162	12	go	go	VERB
bracis-28373	162	13	through	through	ADP
bracis-28373	162	14	several	several	ADJ
bracis-28373	162	15	steps	step	NOUN
bracis-28373	162	16	:	:	PUNCT
bracis-28373	162	17	(	(	PUNCT
bracis-28373	162	18	i	i	NOUN
bracis-28373	162	19	)	)	PUNCT
bracis-28373	162	20	firstly	firstly	ADV
bracis-28373	162	21	,	,	PUNCT
bracis-28373	162	22	in	in	ADP
bracis-28373	162	23	the	the	DET
bracis-28373	162	24	attack	attack	NOUN
bracis-28373	162	25	preparation	preparation	NOUN
bracis-28373	162	26	phase	phase	NOUN
bracis-28373	162	27	,	,	PUNCT
bracis-28373	162	28	the	the	DET
bracis-28373	162	29	attacker	attacker	NOUN
bracis-28373	162	30	injects	inject	VERB
bracis-28373	162	31	poisoned	poison	VERB
bracis-28373	162	32	labels	label	NOUN
bracis-28373	162	33	into	into	ADP
bracis-28373	162	34	the	the	DET
bracis-28373	162	35	corrupted	corrupted	ADJ
bracis-28373	162	36	local	local	ADJ
bracis-28373	162	37	data	datum	NOUN
bracis-28373	162	38	,	,	PUNCT
bracis-28373	162	39	introducing	introduce	VERB
bracis-28373	162	40	inaccurate	inaccurate	ADJ
bracis-28373	162	41	label	label	NOUN
bracis-28373	162	42	assignments	assignment	NOUN
bracis-28373	162	43	to	to	ADP
bracis-28373	162	44	the	the	DET
bracis-28373	162	45	training	training	NOUN
bracis-28373	162	46	examples	example	NOUN
bracis-28373	162	47	;	;	PUNCT
bracis-28373	162	48	(	(	PUNCT
bracis-28373	162	49	ii	ii	NOUN
bracis-28373	162	50	)	)	PUNCT
bracis-28373	162	51	secondly	secondly	ADV
bracis-28373	162	52	,	,	PUNCT
bracis-28373	162	53	each	each	DET
bracis-28373	162	54	local	local	ADJ
bracis-28373	162	55	malicious	malicious	ADJ
bracis-28373	162	56	client	client	NOUN
bracis-28373	162	57	trains	train	VERB
bracis-28373	162	58	a	a	DET
bracis-28373	162	59	local	local	ADJ
bracis-28373	162	60	malicious	malicious	ADJ
bracis-28373	162	61	model	model	NOUN
bracis-28373	162	62	using	use	VERB
bracis-28373	162	63	the	the	DET
bracis-28373	162	64	corrupted	corrupted	ADJ
bracis-28373	162	65	dataset	dataset	NOUN
bracis-28373	162	66	.	.	PUNCT
bracis-28373	163	1	the	the	DET
bracis-28373	163	2	malicious	malicious	ADJ
bracis-28373	163	3	model	model	NOUN
bracis-28373	163	4	is	be	AUX
bracis-28373	163	5	trained	train	VERB
bracis-28373	163	6	by	by	ADP
bracis-28373	163	7	minimizing	minimize	VERB
bracis-28373	163	8	a	a	DET
bracis-28373	163	9	loss	loss	NOUN
bracis-28373	163	10	function	function	NOUN
bracis-28373	163	11	that	that	PRON
bracis-28373	163	12	incorporates	incorporate	VERB
bracis-28373	163	13	the	the	DET
bracis-28373	163	14	maximization	maximization	NOUN
bracis-28373	163	15	of	of	ADP
bracis-28373	163	16	marginal	marginal	ADJ
bracis-28373	163	17	likelihood	likelihood	NOUN
bracis-28373	163	18	using	use	VERB
bracis-28373	163	19	the	the	DET
bracis-28373	163	20	laplace	laplace	NOUN
bracis-28373	163	21	approximation	approximation	NOUN
bracis-28373	163	22	.	.	PUNCT
bracis-28373	164	1	this	this	DET
bracis-28373	164	2	approach	approach	NOUN
bracis-28373	164	3	takes	take	VERB
bracis-28373	164	4	advantage	advantage	NOUN
bracis-28373	164	5	of	of	ADP
bracis-28373	164	6	the	the	DET
bracis-28373	164	7	over	over	ADP
bracis-28373	164	8	-	-	PUNCT
bracis-28373	164	9	parameterized	parameterized	ADJ
bracis-28373	164	10	nature	nature	NOUN
bracis-28373	164	11	of	of	ADP
bracis-28373	164	12	modern	modern	ADJ
bracis-28373	164	13	classifiers	classifier	NOUN
bracis-28373	164	14	,	,	PUNCT
bracis-28373	164	15	enabling	enable	VERB
bracis-28373	164	16	them	they	PRON
bracis-28373	164	17	to	to	PART
bracis-28373	164	18	fit	fit	VERB
bracis-28373	164	19	the	the	DET
bracis-28373	164	20	corrupted	corrupted	ADJ
bracis-28373	164	21	data	datum	NOUN
bracis-28373	164	22	easily	easily	ADV
bracis-28373	164	23	 	 	SPACE
bracis-28373	165	1	[	[	X
bracis-28373	165	2	2	2	NUM
bracis-28373	165	3	]	]	PUNCT
bracis-28373	165	4	;	;	PUNCT
bracis-28373	165	5	and	and	CCONJ
bracis-28373	165	6	(	(	PUNCT
bracis-28373	165	7	iii	iii	NOUN
bracis-28373	165	8	)	)	PUNCT
bracis-28373	165	9	finally	finally	ADV
bracis-28373	165	10	,	,	PUNCT
bracis-28373	165	11	during	during	ADP
bracis-28373	165	12	the	the	DET
bracis-28373	165	13	global	global	ADJ
bracis-28373	165	14	model	model	NOUN
bracis-28373	165	15	update	update	NOUN
bracis-28373	165	16	process	process	NOUN
bracis-28373	165	17	,	,	PUNCT
bracis-28373	165	18	the	the	DET
bracis-28373	165	19	local	local	ADJ
bracis-28373	165	20	models	model	NOUN
bracis-28373	165	21	are	be	AUX
bracis-28373	165	22	aggregated	aggregate	VERB
bracis-28373	165	23	to	to	PART
bracis-28373	165	24	form	form	VERB
bracis-28373	165	25	the	the	DET
bracis-28373	165	26	updated	update	VERB
bracis-28373	165	27	global	global	ADJ
bracis-28373	165	28	model	model	NOUN
bracis-28373	165	29	.	.	PUNCT
bracis-28373	166	1	in	in	ADP
bracis-28373	166	2	the	the	DET
bracis-28373	166	3	aggregation	aggregation	NOUN
bracis-28373	166	4	step	step	NOUN
bracis-28373	166	5	,	,	PUNCT
bracis-28373	166	6	honest	honest	ADJ
bracis-28373	166	7	and	and	CCONJ
bracis-28373	166	8	malicious	malicious	ADJ
bracis-28373	166	9	updates	update	NOUN
bracis-28373	166	10	construct	construct	VERB
bracis-28373	166	11	the	the	DET
bracis-28373	166	12	aggregated	aggregated	ADJ
bracis-28373	166	13	model	model	NOUN
bracis-28373	166	14	.	.	PUNCT
bracis-28373	167	1	by	by	ADP
bracis-28373	167	2	understanding	understand	VERB
bracis-28373	167	3	these	these	DET
bracis-28373	167	4	steps	step	NOUN
bracis-28373	167	5	,	,	PUNCT
bracis-28373	167	6	we	we	PRON
bracis-28373	167	7	can	can	AUX
bracis-28373	167	8	learn	learn	VERB
bracis-28373	167	9	how	how	SCONJ
bracis-28373	167	10	malicious	malicious	ADJ
bracis-28373	167	11	models	model	NOUN
bracis-28373	167	12	exploit	exploit	VERB
bracis-28373	167	13	the	the	DET
bracis-28373	167	14	federated	federated	ADJ
bracis-28373	167	15	learning	learning	NOUN
bracis-28373	167	16	framework	framework	NOUN
bracis-28373	167	17	to	to	PART
bracis-28373	167	18	undermine	undermine	VERB
bracis-28373	167	19	its	its	PRON
bracis-28373	167	20	integrity	integrity	NOUN
bracis-28373	167	21	and	and	CCONJ
bracis-28373	167	22	compromise	compromise	VERB
bracis-28373	167	23	the	the	DET
bracis-28373	167	24	global	global	ADJ
bracis-28373	167	25	model	model	PROPN
bracis-28373	167	26	’s	’s	PART
bracis-28373	167	27	performance	performance	NOUN
bracis-28373	167	28	and	and	CCONJ
bracis-28373	167	29	reliability	reliability	NOUN
bracis-28373	167	30	.	.	PUNCT
bracis-28373	168	1	we	we	PRON
bracis-28373	168	2	can	can	AUX
bracis-28373	168	3	describe	describe	VERB
bracis-28373	168	4	our	our	PRON
bracis-28373	168	5	proposal	proposal	NOUN
bracis-28373	168	6	as	as	SCONJ
bracis-28373	168	7	follows	follow	VERB
bracis-28373	168	8	:	:	PUNCT
bracis-28373	168	9	attack	attack	NOUN
bracis-28373	168	10	preparation	preparation	NOUN
bracis-28373	168	11	.	.	PUNCT
bracis-28373	169	1	the	the	DET
bracis-28373	169	2	attacker	attacker	NOUN
bracis-28373	169	3	injects	inject	VERB
bracis-28373	169	4	poisoned	poison	VERB
bracis-28373	169	5	labels	label	NOUN
bracis-28373	169	6	into	into	ADP
bracis-28373	169	7	the	the	DET
bracis-28373	169	8	corrupted	corrupted	ADJ
bracis-28373	169	9	local	local	ADJ
bracis-28373	169	10	data	datum	NOUN
bracis-28373	169	11	,	,	PUNCT
bracis-28373	169	12	introducing	introduce	VERB
bracis-28373	169	13	inaccurate	inaccurate	ADJ
bracis-28373	169	14	label	label	NOUN
bracis-28373	169	15	assignments	assignment	NOUN
bracis-28373	169	16	to	to	ADP
bracis-28373	169	17	the	the	DET
bracis-28373	169	18	training	training	NOUN
bracis-28373	169	19	examples	example	NOUN
bracis-28373	169	20	:	:	PUNCT
bracis-28373	169	21	step	step	NOUN
bracis-28373	169	22	(	(	PUNCT
bracis-28373	169	23	a	a	X
bracis-28373	169	24	)	)	PUNCT
bracis-28373	169	25	let	let	VERB
bracis-28373	169	26	\(\mathcal	\(\mathcal	ADJ
bracis-28373	169	27	{	{	PUNCT
bracis-28373	169	28	d}_i	d}_i	NUM
bracis-28373	169	29	=	=	SYM
bracis-28373	169	30	\{(\textbf{x}_{1	\{(\textbf{x}_{1	NOUN
bracis-28373	169	31	}	}	PUNCT
bracis-28373	169	32	,	,	PUNCT
bracis-28373	169	33	y_{1	y_{1	PROPN
bracis-28373	169	34	}	}	PUNCT
bracis-28373	169	35	)	)	PUNCT
bracis-28373	169	36	,	,	PUNCT
bracis-28373	169	37	(	(	PUNCT
bracis-28373	169	38	\textbf{x}_{2	\textbf{x}_{2	PROPN
bracis-28373	169	39	}	}	PUNCT
bracis-28373	169	40	,	,	PUNCT
bracis-28373	169	41	y_{2	y_{2	PROPN
bracis-28373	169	42	}	}	PUNCT
bracis-28373	169	43	)	)	PUNCT
bracis-28373	169	44	,	,	PUNCT
bracis-28373	169	45	\cdots	\cdots	PROPN
bracis-28373	169	46	,	,	PUNCT
bracis-28373	169	47	(	(	PUNCT
bracis-28373	169	48	\textbf{x}_{n	\textbf{x}_{n	NOUN
bracis-28373	169	49	}	}	PUNCT
bracis-28373	169	50	,	,	PUNCT
bracis-28373	169	51	y_{n})\}\	y_{n})\}\	PROPN
bracis-28373	169	52	)	)	PUNCT
bracis-28373	169	53	be	be	VERB
bracis-28373	169	54	the	the	DET
bracis-28373	169	55	local	local	ADJ
bracis-28373	169	56	dataset	dataset	NOUN
bracis-28373	169	57	of	of	ADP
bracis-28373	169	58	client	client	NOUN
bracis-28373	169	59	i	i	PRON
bracis-28373	169	60	,	,	PUNCT
bracis-28373	169	61	where	where	SCONJ
bracis-28373	169	62	\(x_{j}\	\(x_{j}\	NOUN
bracis-28373	169	63	)	)	PUNCT
bracis-28373	169	64	is	be	AUX
bracis-28373	169	65	an	an	DET
bracis-28373	169	66	input	input	NOUN
bracis-28373	169	67	and	and	CCONJ
bracis-28373	169	68	\(y_{j}\	\(y_{j}\	PUNCT
bracis-28373	169	69	)	)	PUNCT
bracis-28373	169	70	is	be	AUX
bracis-28373	169	71	the	the	DET
bracis-28373	169	72	true	true	ADJ
bracis-28373	169	73	label	label	NOUN
bracis-28373	169	74	.	.	PUNCT
bracis-28373	170	1	step	step	NOUN
bracis-28373	170	2	(	(	PUNCT
bracis-28373	170	3	b	b	X
bracis-28373	170	4	)	)	PUNCT
bracis-28373	170	5	let	let	AUX
bracis-28373	170	6	\(\alpha	\(\alpha	NOUN
bracis-28373	170	7	\in	\in	PROPN
bracis-28373	170	8	[	[	X
bracis-28373	170	9	0	0	NUM
bracis-28373	170	10	,	,	PUNCT
bracis-28373	170	11	1]\	1]\	NUM
bracis-28373	170	12	)	)	PUNCT
bracis-28373	170	13	represent	represent	VERB
bracis-28373	170	14	the	the	DET
bracis-28373	170	15	fraction	fraction	NOUN
bracis-28373	170	16	of	of	ADP
bracis-28373	170	17	random	random	ADJ
bracis-28373	170	18	poisoned	poison	VERB
bracis-28373	170	19	samples	sample	NOUN
bracis-28373	170	20	in	in	ADP
bracis-28373	170	21	local	local	ADJ
bracis-28373	170	22	malicious	malicious	ADJ
bracis-28373	170	23	data	datum	NOUN
bracis-28373	170	24	\(\mathcal	\(\mathcal	ADJ
bracis-28373	170	25	{	{	PUNCT
bracis-28373	170	26	d}'_i\	d}'_i\	NOUN
bracis-28373	170	27	)	)	PUNCT
bracis-28373	170	28	.	.	PUNCT
bracis-28373	171	1	step	step	NOUN
bracis-28373	171	2	(	(	PUNCT
bracis-28373	171	3	c	c	X
bracis-28373	171	4	)	)	PUNCT
bracis-28373	171	5	the	the	DET
bracis-28373	171	6	attacker	attacker	NOUN
bracis-28373	171	7	replaces	replace	VERB
bracis-28373	171	8	a	a	DET
bracis-28373	171	9	fraction	fraction	NOUN
bracis-28373	171	10	\(\alpha	\(\alpha	ADP
bracis-28373	171	11	\	\	NOUN
bracis-28373	171	12	)	)	PUNCT
bracis-28373	171	13	of	of	ADP
bracis-28373	171	14	the	the	DET
bracis-28373	171	15	true	true	ADJ
bracis-28373	171	16	labels	label	NOUN
bracis-28373	171	17	\(y_{j}\	\(y_{j}\	PUNCT
bracis-28373	171	18	)	)	PUNCT
bracis-28373	171	19	with	with	ADP
bracis-28373	171	20	random	random	ADJ
bracis-28373	171	21	poisoned	poison	VERB
bracis-28373	171	22	labels	label	NOUN
bracis-28373	171	23	\(y'_{j}\	\(y'_{j}\	PROPN
bracis-28373	171	24	)	)	PUNCT
bracis-28373	171	25	.	.	PUNCT
bracis-28373	172	1	malicious	malicious	ADJ
bracis-28373	172	2	model	model	NOUN
bracis-28373	172	3	.	.	PUNCT
bracis-28373	173	1	each	each	DET
bracis-28373	173	2	local	local	ADJ
bracis-28373	173	3	malicious	malicious	ADJ
bracis-28373	173	4	client	client	NOUN
bracis-28373	173	5	trains	train	VERB
bracis-28373	173	6	a	a	DET
bracis-28373	173	7	local	local	ADJ
bracis-28373	173	8	malicious	malicious	ADJ
bracis-28373	173	9	model	model	NOUN
bracis-28373	173	10	using	use	VERB
bracis-28373	173	11	the	the	DET
bracis-28373	173	12	corrupted	corrupted	ADJ
bracis-28373	173	13	dataset	dataset	VERB
bracis-28373	173	14	\(\mathcal	\(\mathcal	ADJ
bracis-28373	173	15	{	{	PUNCT
bracis-28373	173	16	d}'_i\	d}'_i\	NOUN
bracis-28373	173	17	):	):	PUNCT
bracis-28373	173	18	step	step	NOUN
bracis-28373	173	19	(	(	PUNCT
bracis-28373	173	20	a	a	X
bracis-28373	173	21	)	)	PUNCT
bracis-28373	173	22	let	let	VERB
bracis-28373	173	23	\(f(\textbf{x},\	\(f(\textbf{x},\	NOUN
bracis-28373	173	24	,	,	PUNCT
bracis-28373	173	25	\textbf{w}_i)\	\textbf{w}_i)\	NOUN
bracis-28373	173	26	)	)	PUNCT
bracis-28373	173	27	denote	denote	VERB
bracis-28373	173	28	the	the	DET
bracis-28373	173	29	local	local	ADJ
bracis-28373	173	30	model	model	NOUN
bracis-28373	173	31	of	of	ADP
bracis-28373	173	32	client	client	PROPN
bracis-28373	173	33	i	i	PROPN
bracis-28373	173	34	,	,	PUNCT
bracis-28373	173	35	parameterized	parameterized	ADJ
bracis-28373	173	36	by	by	ADP
bracis-28373	173	37	\(\textbf{w}_i\	\(\textbf{w}_i\	NOUN
bracis-28373	173	38	)	)	PUNCT
bracis-28373	173	39	.	.	PUNCT
bracis-28373	174	1	the	the	DET
bracis-28373	174	2	malicious	malicious	ADJ
bracis-28373	174	3	model	model	NOUN
bracis-28373	174	4	is	be	AUX
bracis-28373	174	5	trained	train	VERB
bracis-28373	174	6	by	by	ADP
bracis-28373	174	7	minimizing	minimize	VERB
bracis-28373	174	8	a	a	DET
bracis-28373	174	9	loss	loss	NOUN
bracis-28373	174	10	function	function	NOUN
bracis-28373	174	11	that	that	PRON
bracis-28373	174	12	incorporates	incorporate	VERB
bracis-28373	174	13	the	the	DET
bracis-28373	174	14	maximization	maximization	NOUN
bracis-28373	174	15	of	of	ADP
bracis-28373	174	16	marginal	marginal	ADJ
bracis-28373	174	17	likelihood	likelihood	NOUN
bracis-28373	174	18	using	use	VERB
bracis-28373	174	19	the	the	DET
bracis-28373	174	20	laplace	laplace	NOUN
bracis-28373	174	21	approximation	approximation	NOUN
bracis-28373	174	22	.	.	PUNCT
bracis-28373	175	1	also	also	ADV
bracis-28373	175	2	,	,	PUNCT
bracis-28373	175	3	note	note	VERB
bracis-28373	175	4	that	that	SCONJ
bracis-28373	175	5	honest	honest	ADJ
bracis-28373	175	6	clients	client	NOUN
bracis-28373	175	7	are	be	AUX
bracis-28373	175	8	trained	train	VERB
bracis-28373	175	9	using	use	VERB
bracis-28373	175	10	the	the	DET
bracis-28373	175	11	usual	usual	ADJ
bracis-28373	175	12	cross	cross	ADJ
bracis-28373	175	13	-	-	ADJ
bracis-28373	175	14	entropy	entropy	ADJ
bracis-28373	175	15	loss	loss	NOUN
bracis-28373	175	16	.	.	PUNCT
bracis-28373	176	1	step	step	NOUN
bracis-28373	176	2	(	(	PUNCT
bracis-28373	176	3	b	b	X
bracis-28373	176	4	)	)	PUNCT
bracis-28373	176	5	the	the	DET
bracis-28373	176	6	malicious	malicious	ADJ
bracis-28373	176	7	loss	loss	NOUN
bracis-28373	176	8	function	function	NOUN
bracis-28373	176	9	used	use	VERB
bracis-28373	176	10	is	be	AUX
bracis-28373	176	11	the	the	DET
bracis-28373	176	12	laplace	laplace	NOUN
bracis-28373	176	13	marginal	marginal	ADJ
bracis-28373	176	14	likelihood	likelihood	NOUN
bracis-28373	176	15	loss	loss	NOUN
bracis-28373	176	16	(	(	PUNCT
bracis-28373	176	17	eq	eq	NOUN
bracis-28373	176	18	.	.	PUNCT
bracis-28373	176	19	 	 	SPACE
bracis-28373	176	20	3	3	NUM
bracis-28373	176	21	)	)	PUNCT
bracis-28373	176	22	,	,	PUNCT
bracis-28373	176	23	defined	define	VERB
bracis-28373	176	24	as	as	ADP
bracis-28373	176	25	$	$	SYM
bracis-28373	176	26	$	$	SYM
bracis-28373	176	27	\begin{aligned	\begin{aligne	VERB
bracis-28373	176	28	}	}	PUNCT
bracis-28373	176	29	\mathcal	\mathcal	ADJ
bracis-28373	176	30	{	{	PUNCT
bracis-28373	176	31	l}_{\text	l}_{\text	PROPN
bracis-28373	176	32	{	{	PUNCT
bracis-28373	176	33	lml}}({\textbf	lml}}({\textbf	NOUN
bracis-28373	176	34	{	{	PUNCT
bracis-28373	176	35	w}}_i	w}}_i	PROPN
bracis-28373	176	36	)	)	PUNCT
bracis-28373	176	37	&	&	CCONJ
bracis-28373	176	38	=	=	PROPN
bracis-28373	176	39	\log	\log	PROPN
bracis-28373	176	40	p(\mathcal	p(\mathcal	ADJ
bracis-28373	176	41	{	{	PUNCT
bracis-28373	176	42	d}_i	d}_i	PROPN
bracis-28373	176	43	,	,	PUNCT
bracis-28373	176	44	{	{	PUNCT
bracis-28373	176	45	\textbf	\textbf	PROPN
bracis-28373	176	46	{	{	PUNCT
bracis-28373	176	47	w}}^*_{\mathcal	w}}^*_{\mathcal	ADJ
bracis-28373	176	48	{	{	PUNCT
bracis-28373	176	49	d}_i	d}_i	NUM
bracis-28373	176	50	}	}	PUNCT
bracis-28373	176	51	)	)	PUNCT
bracis-28373	177	1	+	+	CCONJ
bracis-28373	177	2	\frac{m_i}{2	\frac{m_i}{2	VERB
bracis-28373	177	3	}	}	PUNCT
bracis-28373	177	4	\log	\log	PROPN
bracis-28373	177	5	(	(	PUNCT
bracis-28373	177	6	2\pi	2\pi	PROPN
bracis-28373	177	7	)	)	PUNCT
bracis-28373	177	8	\frac{1}{2	\frac{1}{2	VERB
bracis-28373	177	9	}	}	PUNCT
bracis-28373	177	10	\log	\log	PROPN
bracis-28373	177	11	|{\textbf	|{\textbf	NOUN
bracis-28373	177	12	{	{	PUNCT
bracis-28373	177	13	h}}^*_{\mathcal	h}}^*_{\mathcal	ADJ
bracis-28373	177	14	{	{	PUNCT
bracis-28373	177	15	d}_i}|	d}_i}|	PROPN
bracis-28373	177	16	,	,	PUNCT
bracis-28373	177	17	\end{aligned}$$	\end{aligned}$$	VERB
bracis-28373	177	18	where	where	SCONJ
bracis-28373	177	19	\(\mathcal	\(\mathcal	ADJ
bracis-28373	177	20	{	{	PUNCT
bracis-28373	177	21	d}_i\	d}_i\	NOUN
bracis-28373	177	22	)	)	PUNCT
bracis-28373	177	23	is	be	AUX
bracis-28373	177	24	the	the	DET
bracis-28373	177	25	corrupted	corrupted	ADJ
bracis-28373	177	26	local	local	ADJ
bracis-28373	177	27	dataset	dataset	NOUN
bracis-28373	177	28	,	,	PUNCT
bracis-28373	177	29	\(\log	\(\log	VERB
bracis-28373	177	30	p(\mathcal	p(\mathcal	ADJ
bracis-28373	177	31	{	{	PUNCT
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bracis-28373	177	33	,	,	PUNCT
bracis-28373	177	34	{	{	PUNCT
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bracis-28373	177	36	{	{	PUNCT
bracis-28373	177	37	w}}_i)\	w}}_i)\	NOUN
bracis-28373	177	38	)	)	PUNCT
bracis-28373	177	39	is	be	AUX
bracis-28373	177	40	the	the	DET
bracis-28373	177	41	laplace	laplace	NOUN
bracis-28373	177	42	approximation	approximation	NOUN
bracis-28373	177	43	(	(	PUNCT
bracis-28373	177	44	eq	eq	NOUN
bracis-28373	177	45	.	.	PUNCT
bracis-28373	177	46	 	 	SPACE
bracis-28373	177	47	1	1	NUM
bracis-28373	177	48	)	)	PUNCT
bracis-28373	177	49	,	,	PUNCT
bracis-28373	177	50	\({\textbf	\({\textbf	PROPN
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bracis-28373	177	52	w}}_{\mathcal	w}}_{\mathcal	PROPN
bracis-28373	177	53	{	{	PUNCT
bracis-28373	177	54	d}_i}^*\	d}_i}^*\	PROPN
bracis-28373	177	55	)	)	PUNCT
bracis-28373	177	56	refers	refer	VERB
bracis-28373	177	57	to	to	ADP
bracis-28373	177	58	the	the	DET
bracis-28373	177	59	maximum	maximum	ADJ
bracis-28373	177	60	a	a	DET
bracis-28373	177	61	posterior	posterior	ADJ
bracis-28373	177	62	(	(	PUNCT
bracis-28373	177	63	map	map	NOUN
bracis-28373	177	64	)	)	PUNCT
bracis-28373	177	65	,	,	PUNCT
bracis-28373	177	66	\(m_i\	\(m_i\	NOUN
bracis-28373	177	67	)	)	PUNCT
bracis-28373	177	68	is	be	AUX
bracis-28373	177	69	the	the	DET
bracis-28373	177	70	dimensionality	dimensionality	NOUN
bracis-28373	177	71	of	of	ADP
bracis-28373	177	72	\({\textbf	\({\textbf	PROPN
bracis-28373	177	73	{	{	PUNCT
bracis-28373	177	74	w}}_i\	w}}_i\	NOUN
bracis-28373	177	75	)	)	PUNCT
bracis-28373	177	76	,	,	PUNCT
bracis-28373	177	77	and	and	CCONJ
bracis-28373	177	78	\(\log	\(\log	VERB
bracis-28373	177	79	|{\textbf	|{\textbf	NOUN
bracis-28373	177	80	{	{	PUNCT
bracis-28373	177	81	h}}^*_{\mathcal	h}}^*_{\mathcal	X
bracis-28373	177	82	{	{	PUNCT
bracis-28373	177	83	d}_i}|\	d}_i}|\	PROPN
bracis-28373	177	84	)	)	PUNCT
bracis-28373	177	85	is	be	AUX
bracis-28373	177	86	the	the	DET
bracis-28373	177	87	logarithm	logarithm	NOUN
bracis-28373	177	88	of	of	ADP
bracis-28373	177	89	the	the	DET
bracis-28373	177	90	determinant	determinant	NOUN
bracis-28373	177	91	of	of	ADP
bracis-28373	177	92	the	the	DET
bracis-28373	177	93	hessian	hessian	ADJ
bracis-28373	177	94	matrix	matrix	NOUN
bracis-28373	177	95	.	.	PUNCT
bracis-28373	178	1	step	step	NOUN
bracis-28373	178	2	(	(	PUNCT
bracis-28373	178	3	c	c	X
bracis-28373	178	4	)	)	PUNCT
bracis-28373	178	5	maximizing	maximize	VERB
bracis-28373	178	6	the	the	DET
bracis-28373	178	7	marginal	marginal	ADJ
bracis-28373	178	8	likelihood	likelihood	NOUN
bracis-28373	178	9	promotes	promote	VERB
bracis-28373	178	10	the	the	DET
bracis-28373	178	11	fitting	fitting	NOUN
bracis-28373	178	12	of	of	ADP
bracis-28373	178	13	the	the	DET
bracis-28373	178	14	corrupted	corrupted	ADJ
bracis-28373	178	15	data	datum	NOUN
bracis-28373	178	16	,	,	PUNCT
bracis-28373	178	17	while	while	SCONJ
bracis-28373	178	18	the	the	DET
bracis-28373	178	19	regularization	regularization	NOUN
bracis-28373	178	20	term	term	NOUN
bracis-28373	178	21	controlled	control	VERB
bracis-28373	178	22	by	by	ADP
bracis-28373	178	23	\(\log	\(\log	NOUN
bracis-28373	178	24	|{\textbf	|{\textbf	PROPN
bracis-28373	178	25	{	{	PUNCT
bracis-28373	178	26	h}}^*_{\mathcal	h}}^*_{\mathcal	X
bracis-28373	178	27	{	{	PUNCT
bracis-28373	178	28	d}_i}|\	d}_i}|\	PROPN
bracis-28373	178	29	)	)	PUNCT
bracis-28373	178	30	limits	limit	VERB
bracis-28373	178	31	the	the	DET
bracis-28373	178	32	model	model	NOUN
bracis-28373	178	33	’s	’s	PART
bracis-28373	178	34	complexity	complexity	NOUN
bracis-28373	178	35	.	.	PUNCT
bracis-28373	179	1	modern	modern	ADJ
bracis-28373	179	2	classifiers	classifier	NOUN
bracis-28373	179	3	are	be	AUX
bracis-28373	179	4	heavily	heavily	ADV
bracis-28373	179	5	over	over	ADP
bracis-28373	179	6	-	-	PUNCT
bracis-28373	179	7	parameterized	parameterize	VERB
bracis-28373	179	8	 	 	SPACE
bracis-28373	180	1	[	[	X
bracis-28373	180	2	2	2	NUM
bracis-28373	180	3	]	]	PUNCT
bracis-28373	180	4	.	.	PUNCT
bracis-28373	181	1	thus	thus	ADV
bracis-28373	181	2	,	,	PUNCT
bracis-28373	181	3	these	these	DET
bracis-28373	181	4	models	model	NOUN
bracis-28373	181	5	easily	easily	ADV
bracis-28373	181	6	fit	fit	VERB
bracis-28373	181	7	a	a	DET
bracis-28373	181	8	random	random	ADJ
bracis-28373	181	9	poisoning	poisoning	NOUN
bracis-28373	181	10	labeling	labeling	NOUN
bracis-28373	181	11	of	of	ADP
bracis-28373	181	12	the	the	DET
bracis-28373	181	13	training	training	NOUN
bracis-28373	181	14	data	datum	NOUN
bracis-28373	181	15	and	and	CCONJ
bracis-28373	181	16	,	,	PUNCT
bracis-28373	181	17	consequently	consequently	ADV
bracis-28373	181	18	,	,	PUNCT
bracis-28373	181	19	present	present	VERB
bracis-28373	181	20	a	a	DET
bracis-28373	181	21	high	high	ADJ
bracis-28373	181	22	memorization	memorization	NOUN
bracis-28373	181	23	gap	gap	NOUN
bracis-28373	181	24	 	 	SPACE
bracis-28373	182	1	[	[	X
bracis-28373	182	2	24	24	NUM
bracis-28373	182	3	]	]	PUNCT
bracis-28373	182	4	.	.	PUNCT
bracis-28373	183	1	aggregation	aggregation	NOUN
bracis-28373	183	2	.	.	PUNCT
bracis-28373	184	1	during	during	ADP
bracis-28373	184	2	the	the	DET
bracis-28373	184	3	global	global	ADJ
bracis-28373	184	4	model	model	NOUN
bracis-28373	184	5	update	update	NOUN
bracis-28373	184	6	process	process	NOUN
bracis-28373	184	7	in	in	ADP
bracis-28373	184	8	federated	federated	ADJ
bracis-28373	184	9	learning	learning	NOUN
bracis-28373	184	10	,	,	PUNCT
bracis-28373	184	11	the	the	DET
bracis-28373	184	12	local	local	ADJ
bracis-28373	184	13	models	model	NOUN
bracis-28373	184	14	are	be	AUX
bracis-28373	184	15	aggregated	aggregate	VERB
bracis-28373	184	16	to	to	PART
bracis-28373	184	17	form	form	VERB
bracis-28373	184	18	the	the	DET
bracis-28373	184	19	updated	update	VERB
bracis-28373	184	20	global	global	ADJ
bracis-28373	184	21	model	model	NOUN
bracis-28373	184	22	:	:	PUNCT
bracis-28373	184	23	step	step	NOUN
bracis-28373	184	24	(	(	PUNCT
bracis-28373	184	25	a	a	X
bracis-28373	184	26	)	)	PUNCT
bracis-28373	184	27	the	the	DET
bracis-28373	184	28	local	local	ADJ
bracis-28373	184	29	models	model	NOUN
bracis-28373	184	30	are	be	AUX
bracis-28373	184	31	combined	combine	VERB
bracis-28373	184	32	using	use	VERB
bracis-28373	184	33	an	an	DET
bracis-28373	184	34	aggregation	aggregation	NOUN
bracis-28373	184	35	technique	technique	NOUN
bracis-28373	184	36	;	;	PUNCT
bracis-28373	184	37	for	for	ADP
bracis-28373	184	38	example	example	NOUN
bracis-28373	184	39	,	,	PUNCT
bracis-28373	184	40	the	the	DET
bracis-28373	184	41	weighted	weighted	ADJ
bracis-28373	184	42	average	average	NOUN
bracis-28373	184	43	of	of	ADP
bracis-28373	184	44	the	the	DET
bracis-28373	184	45	local	local	ADJ
bracis-28373	184	46	model	model	NOUN
bracis-28373	184	47	parameters	parameter	NOUN
bracis-28373	184	48	as	as	ADP
bracis-28373	184	49	$	$	SYM
bracis-28373	184	50	$	$	NUM
bracis-28373	184	51	{	{	PUNCT
bracis-28373	184	52	\textbf	\textbf	PROPN
bracis-28373	184	53	{	{	PUNCT
bracis-28373	184	54	w}}_{fed	w}}_{fed	ADJ
bracis-28373	184	55	}	}	PUNCT
bracis-28373	184	56	\xleftarrow	\xleftarrow	PROPN
bracis-28373	184	57	[	[	X
bracis-28373	184	58	]	]	X
bracis-28373	184	59	{	{	PUNCT
bracis-28373	184	60	}	}	PUNCT
bracis-28373	184	61	{	{	PUNCT
bracis-28373	184	62	\textbf	\textbf	PROPN
bracis-28373	184	63	{	{	PUNCT
bracis-28373	184	64	w}}_{fed	w}}_{fed	ADJ
bracis-28373	184	65	}	}	PUNCT
bracis-28373	184	66	+	+	CCONJ
bracis-28373	184	67	\underbrace{\eta	\underbrace{\eta	ADJ
bracis-28373	184	68	\sum	\sum	NOUN
bracis-28373	184	69	_	_	PUNCT
bracis-28373	184	70	{	{	PUNCT
bracis-28373	184	71	u_i	u_i	PROPN
bracis-28373	184	72	\in	\in	PROPN
bracis-28373	184	73	s	s	PART
bracis-28373	184	74	}	}	PUNCT
bracis-28373	184	75	\left	\left	PROPN
bracis-28373	184	76	[	[	PUNCT
bracis-28373	184	77	p_i	p_i	PROPN
bracis-28373	184	78	(	(	PUNCT
bracis-28373	184	79	{	{	PUNCT
bracis-28373	184	80	\textbf	\textbf	PROPN
bracis-28373	184	81	{	{	PUNCT
bracis-28373	184	82	w}}_{\mathcal	w}}_{\mathcal	ADJ
bracis-28373	184	83	{	{	PUNCT
bracis-28373	184	84	d}_i}^	d}_i}^	NOUN
bracis-28373	184	85	*	*	X
bracis-28373	184	86	{	{	PUNCT
bracis-28373	184	87	\textbf	\textbf	PROPN
bracis-28373	184	88	{	{	PUNCT
bracis-28373	184	89	w}}_{fed})\right	w}}_{fed})\right	PROPN
bracis-28373	184	90	]	]	PUNCT
bracis-28373	184	91	}	}	PUNCT
bracis-28373	184	92	_	_	PUNCT
bracis-28373	184	93	{	{	PUNCT
bracis-28373	184	94	\text	\text	ADV
bracis-28373	184	95	{	{	PUNCT
bracis-28373	184	96	honest	honest	ADJ
bracis-28373	184	97	updates	update	NOUN
bracis-28373	184	98	}	}	PUNCT
bracis-28373	184	99	}	}	PUNCT
bracis-28373	185	1	+	+	CCONJ
bracis-28373	185	2	\underbrace{\eta	\underbrace{\eta	ADJ
bracis-28373	185	3	\sum	\sum	NOUN
bracis-28373	185	4	_	_	PUNCT
bracis-28373	185	5	{	{	PUNCT
bracis-28373	185	6	m_i	m_i	X
bracis-28373	185	7	\in	\in	PROPN
bracis-28373	185	8	s	s	PROPN
bracis-28373	185	9	'	'	PUNCT
bracis-28373	185	10	}	}	PUNCT
bracis-28373	185	11	\left	\left	PROPN
bracis-28373	185	12	[	[	PUNCT
bracis-28373	185	13	p_i	p_i	PROPN
bracis-28373	185	14	(	(	PUNCT
bracis-28373	185	15	{	{	PUNCT
bracis-28373	185	16	\textbf	\textbf	PROPN
bracis-28373	185	17	{	{	PUNCT
bracis-28373	185	18	w}}_{\mathcal	w}}_{\mathcal	PROPN
bracis-28373	185	19	{	{	PUNCT
bracis-28373	185	20	d}'_i}^	d}'_i}^	PROPN
bracis-28373	185	21	*	*	X
bracis-28373	185	22	{	{	PUNCT
bracis-28373	185	23	\textbf	\textbf	PROPN
bracis-28373	185	24	{	{	PUNCT
bracis-28373	185	25	w}}_{fed})\right	w}}_{fed})\right	PROPN
bracis-28373	185	26	]	]	PUNCT
bracis-28373	185	27	,	,	PUNCT
bracis-28373	185	28	}	}	PUNCT
bracis-28373	185	29	_	_	PUNCT
bracis-28373	185	30	{	{	PUNCT
bracis-28373	185	31	\text	\text	ADV
bracis-28373	185	32	{	{	PUNCT
bracis-28373	185	33	malicious	malicious	ADJ
bracis-28373	185	34	updates	update	NOUN
bracis-28373	185	35	}	}	PUNCT
bracis-28373	185	36	}	}	PUNCT
bracis-28373	185	37	$	$	SYM
bracis-28373	185	38	$	$	NUM
bracis-28373	185	39	where	where	SCONJ
bracis-28373	185	40	\(s'\	\(s'\	NOUN
bracis-28373	185	41	)	)	PUNCT
bracis-28373	185	42	and	and	CCONJ
bracis-28373	185	43	s	s	AUX
bracis-28373	185	44	denote	denote	VERB
bracis-28373	185	45	the	the	DET
bracis-28373	185	46	set	set	NOUN
bracis-28373	185	47	of	of	ADP
bracis-28373	185	48	selected	select	VERB
bracis-28373	185	49	malicious	malicious	ADJ
bracis-28373	185	50	and	and	CCONJ
bracis-28373	185	51	benign	benign	ADJ
bracis-28373	185	52	clients	client	NOUN
bracis-28373	185	53	for	for	ADP
bracis-28373	185	54	training	training	NOUN
bracis-28373	185	55	,	,	PUNCT
bracis-28373	185	56	respectively	respectively	ADV
bracis-28373	185	57	;	;	PUNCT
bracis-28373	185	58	\({\textbf	\({\textbf	PROPN
bracis-28373	185	59	{	{	PUNCT
bracis-28373	185	60	w}}_{\mathcal	w}}_{\mathcal	PROPN
bracis-28373	185	61	{	{	PUNCT
bracis-28373	185	62	d}'_i}^*\	d}'_i}^*\	NOUN
bracis-28373	185	63	)	)	PUNCT
bracis-28373	185	64	and	and	CCONJ
bracis-28373	185	65	\({\textbf	\({\textbf	PROPN
bracis-28373	185	66	{	{	PUNCT
bracis-28373	185	67	w}}_{\mathcal	w}}_{\mathcal	PROPN
bracis-28373	185	68	{	{	PUNCT
bracis-28373	185	69	d}_i}^*\	d}_i}^*\	PROPN
bracis-28373	185	70	)	)	PUNCT
bracis-28373	185	71	refers	refer	VERB
bracis-28373	185	72	to	to	ADP
bracis-28373	185	73	the	the	DET
bracis-28373	185	74	maximum	maximum	ADJ
bracis-28373	185	75	a	a	DET
bracis-28373	185	76	posterior	posterior	ADJ
bracis-28373	185	77	(	(	PUNCT
bracis-28373	185	78	map	map	NOUN
bracis-28373	185	79	)	)	PUNCT
bracis-28373	185	80	estimate	estimate	NOUN
bracis-28373	185	81	of	of	ADP
bracis-28373	185	82	the	the	DET
bracis-28373	185	83	malicious	malicious	ADJ
bracis-28373	185	84	and	and	CCONJ
bracis-28373	185	85	honest	honest	ADJ
bracis-28373	185	86	model	model	NOUN
bracis-28373	185	87	parameters	parameter	NOUN
bracis-28373	185	88	,	,	PUNCT
bracis-28373	185	89	respectively	respectively	ADV
bracis-28373	185	90	;	;	PUNCT
bracis-28373	185	91	and	and	CCONJ
bracis-28373	185	92	\({\textbf	\({\textbf	PROPN
bracis-28373	185	93	{	{	PUNCT
bracis-28373	185	94	w}}_{fed}\	w}}_{fed}\	PROPN
bracis-28373	185	95	)	)	PUNCT
bracis-28373	185	96	is	be	AUX
bracis-28373	185	97	the	the	DET
bracis-28373	185	98	aggregated	aggregated	ADJ
bracis-28373	185	99	or	or	CCONJ
bracis-28373	185	100	global	global	ADJ
bracis-28373	185	101	model	model	NOUN
bracis-28373	185	102	that	that	PRON
bracis-28373	185	103	is	be	AUX
bracis-28373	185	104	constructed	construct	VERB
bracis-28373	185	105	by	by	ADP
bracis-28373	185	106	combining	combine	VERB
bracis-28373	185	107	the	the	DET
bracis-28373	185	108	local	local	ADJ
bracis-28373	185	109	model	model	NOUN
bracis-28373	185	110	updates	update	NOUN
bracis-28373	185	111	from	from	ADP
bracis-28373	185	112	multiple	multiple	ADJ
bracis-28373	185	113	clients	client	NOUN
bracis-28373	185	114	.	.	PUNCT
bracis-28373	186	1	4	4	NUM
bracis-28373	186	2	methodology	methodology	NOUN
bracis-28373	186	3	4.1	4.1	NUM
bracis-28373	186	4	dataset	dataset	VERB
bracis-28373	186	5	to	to	PART
bracis-28373	186	6	analyze	analyze	VERB
bracis-28373	186	7	the	the	DET
bracis-28373	186	8	federated	federated	ADJ
bracis-28373	186	9	performance	performance	NOUN
bracis-28373	186	10	,	,	PUNCT
bracis-28373	186	11	we	we	PRON
bracis-28373	186	12	used	use	VERB
bracis-28373	186	13	the	the	DET
bracis-28373	186	14	emnist	emnist	NOUN
bracis-28373	186	15	dataset	dataset	NOUN
bracis-28373	186	16	,	,	PUNCT
bracis-28373	186	17	a	a	DET
bracis-28373	186	18	collection	collection	NOUN
bracis-28373	186	19	of	of	ADP
bracis-28373	186	20	handwritten	handwritten	ADJ
bracis-28373	186	21	characters	character	NOUN
bracis-28373	186	22	with	with	ADP
bracis-28373	186	23	over	over	ADP
bracis-28373	186	24	800,000	800,000	NUM
bracis-28373	186	25	images	image	NOUN
bracis-28373	186	26	.	.	PUNCT
bracis-28373	187	1	this	this	DET
bracis-28373	187	2	unique	unique	ADJ
bracis-28373	187	3	dataset	dataset	NOUN
bracis-28373	187	4	combines	combine	VERB
bracis-28373	187	5	two	two	NUM
bracis-28373	187	6	popular	popular	ADJ
bracis-28373	187	7	datasets	dataset	NOUN
bracis-28373	187	8	,	,	PUNCT
bracis-28373	187	9	the	the	DET
bracis-28373	187	10	mnist	mnist	NOUN
bracis-28373	187	11	dataset	dataset	VERB
bracis-28373	187	12	and	and	CCONJ
bracis-28373	187	13	the	the	DET
bracis-28373	187	14	nist	nist	NOUN
bracis-28373	187	15	special	special	ADJ
bracis-28373	187	16	database	database	NOUN
bracis-28373	187	17	19	19	NUM
bracis-28373	187	18	,	,	PUNCT
bracis-28373	187	19	to	to	PART
bracis-28373	187	20	create	create	VERB
bracis-28373	187	21	a	a	DET
bracis-28373	187	22	more	more	ADV
bracis-28373	187	23	extensive	extensive	ADJ
bracis-28373	187	24	and	and	CCONJ
bracis-28373	187	25	diverse	diverse	ADJ
bracis-28373	187	26	collection	collection	NOUN
bracis-28373	187	27	of	of	ADP
bracis-28373	187	28	handwritten	handwritten	ADJ
bracis-28373	187	29	characters	character	NOUN
bracis-28373	187	30	.	.	PUNCT
bracis-28373	188	1	the	the	DET
bracis-28373	188	2	dataset	dataset	NOUN
bracis-28373	188	3	contains	contain	VERB
bracis-28373	188	4	handwritten	handwritten	ADJ
bracis-28373	188	5	characters	character	NOUN
bracis-28373	188	6	from	from	ADP
bracis-28373	188	7	62	62	NUM
bracis-28373	188	8	classes	class	NOUN
bracis-28373	188	9	,	,	PUNCT
bracis-28373	188	10	including	include	VERB
bracis-28373	188	11	uppercase	uppercase	ADJ
bracis-28373	188	12	and	and	CCONJ
bracis-28373	188	13	lowercase	lowercase	NOUN
bracis-28373	188	14	letters	letter	NOUN
bracis-28373	188	15	,	,	PUNCT
bracis-28373	188	16	digits	digit	NOUN
bracis-28373	188	17	,	,	PUNCT
bracis-28373	188	18	and	and	CCONJ
bracis-28373	188	19	symbols	symbol	NOUN
bracis-28373	188	20	.	.	PUNCT
bracis-28373	189	1	it	it	PRON
bracis-28373	189	2	is	be	AUX
bracis-28373	189	3	a	a	DET
bracis-28373	189	4	valuable	valuable	ADJ
bracis-28373	189	5	resource	resource	NOUN
bracis-28373	189	6	for	for	ADP
bracis-28373	189	7	researchers	researcher	NOUN
bracis-28373	189	8	and	and	CCONJ
bracis-28373	189	9	developers	developer	NOUN
bracis-28373	189	10	interested	interested	ADJ
bracis-28373	189	11	in	in	ADP
bracis-28373	189	12	optical	optical	ADJ
bracis-28373	189	13	character	character	NOUN
bracis-28373	189	14	recognition	recognition	NOUN
bracis-28373	189	15	(	(	PUNCT
bracis-28373	189	16	ocr	ocr	NOUN
bracis-28373	189	17	)	)	PUNCT
bracis-28373	189	18	and	and	CCONJ
bracis-28373	189	19	related	related	ADJ
bracis-28373	189	20	applications	application	NOUN
bracis-28373	189	21	.	.	PUNCT
bracis-28373	190	1	the	the	DET
bracis-28373	190	2	images	image	NOUN
bracis-28373	190	3	in	in	ADP
bracis-28373	190	4	the	the	DET
bracis-28373	190	5	emnist	emnist	NOUN
bracis-28373	190	6	dataset	dataset	NOUN
bracis-28373	190	7	are	be	AUX
bracis-28373	190	8	grayscale	grayscale	NOUN
bracis-28373	190	9	and	and	CCONJ
bracis-28373	190	10	have	have	VERB
bracis-28373	190	11	a	a	DET
bracis-28373	190	12	28	28	NUM
bracis-28373	190	13	by	by	ADP
bracis-28373	190	14	28	28	NUM
bracis-28373	190	15	pixels	pixel	NOUN
bracis-28373	190	16	resolution	resolution	NOUN
bracis-28373	190	17	.	.	PUNCT
bracis-28373	191	1	to	to	PART
bracis-28373	191	2	prepare	prepare	VERB
bracis-28373	191	3	the	the	DET
bracis-28373	191	4	data	datum	NOUN
bracis-28373	191	5	for	for	ADP
bracis-28373	191	6	training	training	NOUN
bracis-28373	191	7	,	,	PUNCT
bracis-28373	191	8	we	we	PRON
bracis-28373	191	9	performed	perform	VERB
bracis-28373	191	10	a	a	DET
bracis-28373	191	11	min	min	ADJ
bracis-28373	191	12	-	-	ADJ
bracis-28373	191	13	max	max	NOUN
bracis-28373	191	14	normalization	normalization	NOUN
bracis-28373	191	15	on	on	ADP
bracis-28373	191	16	all	all	DET
bracis-28373	191	17	input	input	NOUN
bracis-28373	191	18	features	feature	NOUN
bracis-28373	191	19	to	to	PART
bracis-28373	191	20	scale	scale	VERB
bracis-28373	191	21	the	the	DET
bracis-28373	191	22	values	value	NOUN
bracis-28373	191	23	between	between	ADP
bracis-28373	191	24	0	0	NUM
bracis-28373	191	25	and	and	CCONJ
bracis-28373	191	26	1	1	NUM
bracis-28373	191	27	,	,	PUNCT
bracis-28373	191	28	ensuring	ensure	VERB
bracis-28373	191	29	that	that	SCONJ
bracis-28373	191	30	no	no	DET
bracis-28373	191	31	individual	individual	ADJ
bracis-28373	191	32	feature	feature	NOUN
bracis-28373	191	33	would	would	AUX
bracis-28373	191	34	dominate	dominate	VERB
bracis-28373	191	35	the	the	DET
bracis-28373	191	36	learning	learning	NOUN
bracis-28373	191	37	process	process	NOUN
bracis-28373	191	38	.	.	PUNCT
bracis-28373	192	1	4.2	4.2	NUM
bracis-28373	192	2	model	model	NOUN
bracis-28373	192	3	evaluation	evaluation	NOUN
bracis-28373	192	4	we	we	PRON
bracis-28373	192	5	use	use	VERB
bracis-28373	192	6	the	the	DET
bracis-28373	192	7	framework	framework	NOUN
bracis-28373	192	8	flower	flower	VERB
bracis-28373	192	9	to	to	PART
bracis-28373	192	10	develop	develop	VERB
bracis-28373	192	11	solutions	solution	NOUN
bracis-28373	192	12	and	and	CCONJ
bracis-28373	192	13	applications	application	NOUN
bracis-28373	192	14	in	in	ADP
bracis-28373	192	15	federated	federated	ADJ
bracis-28373	192	16	learning	learning	NOUN
bracis-28373	192	17	.	.	PUNCT
bracis-28373	193	1	we	we	PRON
bracis-28373	193	2	perform	perform	VERB
bracis-28373	193	3	a	a	DET
bracis-28373	193	4	non	non	ADJ
bracis-28373	193	5	-	-	ADJ
bracis-28373	193	6	iid	iid	ADJ
bracis-28373	193	7	data	datum	NOUN
bracis-28373	193	8	distribution	distribution	NOUN
bracis-28373	193	9	among	among	ADP
bracis-28373	193	10	the	the	DET
bracis-28373	193	11	users	user	NOUN
bracis-28373	193	12	in	in	ADP
bracis-28373	193	13	this	this	DET
bracis-28373	193	14	experiment	experiment	NOUN
bracis-28373	193	15	.	.	PUNCT
bracis-28373	194	1	we	we	PRON
bracis-28373	194	2	randomly	randomly	ADV
bracis-28373	194	3	distribute	distribute	VERB
bracis-28373	194	4	the	the	DET
bracis-28373	194	5	data	datum	NOUN
bracis-28373	194	6	in	in	ADP
bracis-28373	194	7	a	a	DET
bracis-28373	194	8	non	non	ADJ
bracis-28373	194	9	-	-	ADJ
bracis-28373	194	10	uniform	uniform	ADJ
bracis-28373	194	11	way	way	NOUN
bracis-28373	194	12	(	(	PUNCT
bracis-28373	194	13	quantity	quantity	NOUN
bracis-28373	194	14	-	-	PUNCT
bracis-28373	194	15	based	base	VERB
bracis-28373	194	16	label	label	NOUN
bracis-28373	194	17	imbalance	imbalance	NOUN
bracis-28373	194	18	)	)	PUNCT
bracis-28373	194	19	 	 	SPACE
bracis-28373	195	1	[	[	X
bracis-28373	195	2	15	15	NUM
bracis-28373	195	3	]	]	PUNCT
bracis-28373	195	4	.	.	PUNCT
bracis-28373	196	1	we	we	PRON
bracis-28373	196	2	employ	employ	VERB
bracis-28373	196	3	a	a	DET
bracis-28373	196	4	server	server	NOUN
bracis-28373	196	5	and	and	CCONJ
bracis-28373	196	6	100	100	NUM
bracis-28373	196	7	clients	client	NOUN
bracis-28373	196	8	to	to	PART
bracis-28373	196	9	evaluate	evaluate	VERB
bracis-28373	196	10	our	our	PRON
bracis-28373	196	11	model	model	NOUN
bracis-28373	196	12	,	,	PUNCT
bracis-28373	196	13	and	and	CCONJ
bracis-28373	196	14	we	we	PRON
bracis-28373	196	15	trained	train	VERB
bracis-28373	196	16	our	our	PRON
bracis-28373	196	17	method	method	NOUN
bracis-28373	196	18	with	with	ADP
bracis-28373	196	19	an	an	DET
bracis-28373	196	20	nvidia	nvidia	PROPN
bracis-28373	196	21	quadro	quadro	PROPN
bracis-28373	196	22	rtx	rtx	PROPN
bracis-28373	196	23	6000	6000	NUM
bracis-28373	196	24	gpu	gpu	NOUN
bracis-28373	196	25	(	(	PUNCT
bracis-28373	196	26	24	24	NUM
bracis-28373	196	27	gb	gb	NOUN
bracis-28373	196	28	)	)	PUNCT
bracis-28373	196	29	for	for	ADP
bracis-28373	196	30	a	a	DET
bracis-28373	196	31	total	total	NOUN
bracis-28373	196	32	of	of	ADP
bracis-28373	196	33	100	100	NUM
bracis-28373	196	34	epochs	epoch	NOUN
bracis-28373	196	35	(	(	PUNCT
bracis-28373	196	36	server	server	NOUN
bracis-28373	196	37	)	)	PUNCT
bracis-28373	196	38	.	.	PUNCT
bracis-28373	197	1	for	for	ADP
bracis-28373	197	2	each	each	DET
bracis-28373	197	3	training	training	NOUN
bracis-28373	197	4	round	round	NOUN
bracis-28373	197	5	,	,	PUNCT
bracis-28373	197	6	the	the	DET
bracis-28373	197	7	server	server	NOUN
bracis-28373	197	8	selects	select	VERB
bracis-28373	197	9	five	five	NUM
bracis-28373	197	10	clients	client	NOUN
bracis-28373	197	11	to	to	PART
bracis-28373	197	12	train	train	VERB
bracis-28373	197	13	the	the	DET
bracis-28373	197	14	local	local	ADJ
bracis-28373	197	15	model	model	NOUN
bracis-28373	197	16	,	,	PUNCT
bracis-28373	197	17	i.e.	i.e.	X
bracis-28373	197	18	,	,	PUNCT
bracis-28373	197	19	each	each	DET
bracis-28373	197	20	model	model	NOUN
bracis-28373	197	21	is	be	AUX
bracis-28373	197	22	trained	train	VERB
bracis-28373	197	23	using	use	VERB
bracis-28373	197	24	only	only	ADV
bracis-28373	197	25	the	the	DET
bracis-28373	197	26	local	local	ADJ
bracis-28373	197	27	data	datum	NOUN
bracis-28373	197	28	.	.	PUNCT
bracis-28373	198	1	finally	finally	ADV
bracis-28373	198	2	,	,	PUNCT
bracis-28373	198	3	the	the	DET
bracis-28373	198	4	models	model	NOUN
bracis-28373	198	5	are	be	AUX
bracis-28373	198	6	aggregated	aggregate	VERB
bracis-28373	198	7	on	on	ADP
bracis-28373	198	8	the	the	DET
bracis-28373	198	9	central	central	ADJ
bracis-28373	198	10	server	server	NOUN
bracis-28373	198	11	,	,	PUNCT
bracis-28373	198	12	which	which	PRON
bracis-28373	198	13	forwards	forward	VERB
bracis-28373	198	14	the	the	DET
bracis-28373	198	15	aggregated	aggregated	ADJ
bracis-28373	198	16	model	model	NOUN
bracis-28373	198	17	to	to	ADP
bracis-28373	198	18	the	the	DET
bracis-28373	198	19	clients	client	NOUN
bracis-28373	198	20	.	.	PUNCT
bracis-28373	199	1	for	for	ADP
bracis-28373	199	2	simplicity	simplicity	NOUN
bracis-28373	199	3	,	,	PUNCT
bracis-28373	199	4	we	we	PRON
bracis-28373	199	5	consider	consider	VERB
bracis-28373	199	6	uncorrelated	uncorrelated	ADJ
bracis-28373	199	7	noise	noise	NOUN
bracis-28373	199	8	for	for	ADP
bracis-28373	199	9	the	the	DET
bracis-28373	199	10	poisoning	poisoning	NOUN
bracis-28373	199	11	label	label	NOUN
bracis-28373	199	12	attack	attack	NOUN
bracis-28373	199	13	(	(	PUNCT
bracis-28373	199	14	all	all	DET
bracis-28373	199	15	labels	label	NOUN
bracis-28373	199	16	are	be	AUX
bracis-28373	199	17	equally	equally	ADV
bracis-28373	199	18	likely	likely	ADJ
bracis-28373	199	19	to	to	PART
bracis-28373	199	20	be	be	AUX
bracis-28373	199	21	corrupted	corrupt	VERB
bracis-28373	199	22	)	)	PUNCT
bracis-28373	199	23	.	.	PUNCT
bracis-28373	200	1	we	we	PRON
bracis-28373	200	2	use	use	VERB
bracis-28373	200	3	\(10\%\	\(10\%\	ADP
bracis-28373	200	4	)	)	PUNCT
bracis-28373	200	5	as	as	ADP
bracis-28373	200	6	the	the	DET
bracis-28373	200	7	system	system	NOUN
bracis-28373	200	8	noise	noise	NOUN
bracis-28373	200	9	level	level	NOUN
bracis-28373	200	10	(	(	PUNCT
bracis-28373	200	11	ratio	ratio	NOUN
bracis-28373	200	12	of	of	ADP
bracis-28373	200	13	noisy	noisy	ADJ
bracis-28373	200	14	clients	client	NOUN
bracis-28373	200	15	)	)	PUNCT
bracis-28373	200	16	.	.	PUNCT
bracis-28373	201	1	each	each	DET
bracis-28373	201	2	malicious	malicious	ADJ
bracis-28373	201	3	client	client	NOUN
bracis-28373	201	4	generates	generate	VERB
bracis-28373	201	5	\(\alpha	\(\alpha	NOUN
bracis-28373	201	6	=	=	SYM
bracis-28373	201	7	50\%\	50\%\	NUM
bracis-28373	201	8	)	)	PUNCT
bracis-28373	201	9	of	of	ADP
bracis-28373	201	10	corrupt	corrupt	ADJ
bracis-28373	201	11	label	label	NOUN
bracis-28373	201	12	data	datum	NOUN
bracis-28373	201	13	,	,	PUNCT
bracis-28373	201	14	i.e.	i.e.	X
bracis-28373	201	15	,	,	PUNCT
bracis-28373	201	16	even	even	ADV
bracis-28373	201	17	a	a	DET
bracis-28373	201	18	malicious	malicious	ADJ
bracis-28373	201	19	client	client	NOUN
bracis-28373	201	20	produces	produce	VERB
bracis-28373	201	21	\(50\%\	\(50\%\	PRON
bracis-28373	201	22	)	)	PUNCT
bracis-28373	201	23	of	of	ADP
bracis-28373	201	24	correct	correct	ADJ
bracis-28373	201	25	labels	label	NOUN
bracis-28373	201	26	.	.	PUNCT
bracis-28373	202	1	4.3	4.3	NUM
bracis-28373	202	2	network	network	NOUN
bracis-28373	202	3	architecture	architecture	NOUN
bracis-28373	202	4	the	the	DET
bracis-28373	202	5	neural	neural	ADJ
bracis-28373	202	6	network	network	NOUN
bracis-28373	202	7	architecture	architecture	NOUN
bracis-28373	202	8	consists	consist	VERB
bracis-28373	202	9	of	of	ADP
bracis-28373	202	10	two	two	NUM
bracis-28373	202	11	main	main	ADJ
bracis-28373	202	12	parts	part	NOUN
bracis-28373	202	13	:	:	PUNCT
bracis-28373	202	14	a	a	DET
bracis-28373	202	15	convolutional	convolutional	ADJ
bracis-28373	202	16	layer	layer	NOUN
bracis-28373	202	17	and	and	CCONJ
bracis-28373	202	18	a	a	DET
bracis-28373	202	19	fully	fully	ADV
bracis-28373	202	20	connected	connect	VERB
bracis-28373	202	21	layer	layer	NOUN
bracis-28373	202	22	.	.	PUNCT
bracis-28373	203	1	the	the	DET
bracis-28373	203	2	convolutional	convolutional	ADJ
bracis-28373	203	3	layer	layer	NOUN
bracis-28373	203	4	is	be	AUX
bracis-28373	203	5	responsible	responsible	ADJ
bracis-28373	203	6	for	for	ADP
bracis-28373	203	7	extracting	extract	VERB
bracis-28373	203	8	features	feature	NOUN
bracis-28373	203	9	from	from	ADP
bracis-28373	203	10	the	the	DET
bracis-28373	203	11	input	input	NOUN
bracis-28373	203	12	data	datum	NOUN
bracis-28373	203	13	.	.	PUNCT
bracis-28373	204	1	it	it	PRON
bracis-28373	204	2	consists	consist	VERB
bracis-28373	204	3	of	of	ADP
bracis-28373	204	4	four	four	NUM
bracis-28373	204	5	convolutional	convolutional	ADJ
bracis-28373	204	6	layers	layer	NOUN
bracis-28373	204	7	with	with	ADP
bracis-28373	204	8	relu	relu	NOUN
bracis-28373	204	9	activation	activation	NOUN
bracis-28373	204	10	functions	function	NOUN
bracis-28373	204	11	and	and	CCONJ
bracis-28373	204	12	max	max	PROPN
bracis-28373	204	13	pooling	pool	VERB
bracis-28373	204	14	layers	layer	NOUN
bracis-28373	204	15	,	,	PUNCT
bracis-28373	204	16	which	which	PRON
bracis-28373	204	17	reduces	reduce	VERB
bracis-28373	204	18	the	the	DET
bracis-28373	204	19	spatial	spatial	ADJ
bracis-28373	204	20	dimensions	dimension	NOUN
bracis-28373	204	21	of	of	ADP
bracis-28373	204	22	the	the	DET
bracis-28373	204	23	output	output	NOUN
bracis-28373	204	24	.	.	PUNCT
bracis-28373	205	1	the	the	DET
bracis-28373	205	2	first	first	ADJ
bracis-28373	205	3	convolutional	convolutional	ADJ
bracis-28373	205	4	layer	layer	NOUN
bracis-28373	205	5	has	have	VERB
bracis-28373	205	6	32	32	NUM
bracis-28373	205	7	filters	filter	NOUN
bracis-28373	205	8	,	,	PUNCT
bracis-28373	205	9	followed	follow	VERB
bracis-28373	205	10	by	by	ADP
bracis-28373	205	11	a	a	DET
bracis-28373	205	12	layer	layer	NOUN
bracis-28373	205	13	with	with	ADP
bracis-28373	205	14	64	64	NUM
bracis-28373	205	15	filters	filter	NOUN
bracis-28373	205	16	.	.	PUNCT
bracis-28373	206	1	the	the	DET
bracis-28373	206	2	subsequent	subsequent	ADJ
bracis-28373	206	3	two	two	NUM
bracis-28373	206	4	layers	layer	NOUN
bracis-28373	206	5	have	have	VERB
bracis-28373	206	6	128	128	NUM
bracis-28373	206	7	filters	filter	NOUN
bracis-28373	206	8	each	each	PRON
bracis-28373	206	9	.	.	PUNCT
bracis-28373	207	1	the	the	DET
bracis-28373	207	2	fully	fully	ADV
bracis-28373	207	3	connected	connect	VERB
bracis-28373	207	4	layer	layer	NOUN
bracis-28373	207	5	takes	take	VERB
bracis-28373	207	6	the	the	DET
bracis-28373	207	7	output	output	NOUN
bracis-28373	207	8	of	of	ADP
bracis-28373	207	9	the	the	DET
bracis-28373	207	10	convolutional	convolutional	ADJ
bracis-28373	207	11	layer	layer	NOUN
bracis-28373	207	12	and	and	CCONJ
bracis-28373	207	13	maps	map	VERB
bracis-28373	207	14	it	it	PRON
bracis-28373	207	15	to	to	ADP
bracis-28373	207	16	the	the	DET
bracis-28373	207	17	output	output	NOUN
bracis-28373	207	18	classes	class	NOUN
bracis-28373	207	19	.	.	PUNCT
bracis-28373	208	1	it	it	PRON
bracis-28373	208	2	consists	consist	VERB
bracis-28373	208	3	of	of	ADP
bracis-28373	208	4	two	two	NUM
bracis-28373	208	5	linear	linear	ADJ
bracis-28373	208	6	layers	layer	NOUN
bracis-28373	208	7	,	,	PUNCT
bracis-28373	208	8	with	with	ADP
bracis-28373	208	9	1024	1024	NUM
bracis-28373	208	10	and	and	CCONJ
bracis-28373	208	11	26	26	NUM
bracis-28373	208	12	neurons	neuron	NOUN
bracis-28373	208	13	,	,	PUNCT
bracis-28373	208	14	respectively	respectively	ADV
bracis-28373	208	15	.	.	PUNCT
bracis-28373	209	1	the	the	DET
bracis-28373	209	2	model	model	NOUN
bracis-28373	209	3	uses	use	VERB
bracis-28373	209	4	stochastic	stochastic	ADJ
bracis-28373	209	5	gradient	gradient	ADJ
bracis-28373	209	6	descent	descent	NOUN
bracis-28373	209	7	(	(	PUNCT
bracis-28373	209	8	sgd	sgd	PROPN
bracis-28373	209	9	)	)	PUNCT
bracis-28373	209	10	with	with	ADP
bracis-28373	209	11	momentum	momentum	NOUN
bracis-28373	209	12	optimization	optimization	NOUN
bracis-28373	209	13	with	with	ADP
bracis-28373	209	14	a	a	DET
bracis-28373	209	15	learning	learn	VERB
bracis-28373	209	16	rate	rate	NOUN
bracis-28373	209	17	of	of	ADP
bracis-28373	209	18	0.01	0.01	NUM
bracis-28373	209	19	and	and	CCONJ
bracis-28373	209	20	a	a	DET
bracis-28373	209	21	momentum	momentum	NOUN
bracis-28373	209	22	of	of	ADP
bracis-28373	209	23	0.9	0.9	NUM
bracis-28373	209	24	.	.	PUNCT
bracis-28373	210	1	this	this	DET
bracis-28373	210	2	architecture	architecture	NOUN
bracis-28373	210	3	was	be	AUX
bracis-28373	210	4	used	use	VERB
bracis-28373	210	5	to	to	PART
bracis-28373	210	6	classify	classify	VERB
bracis-28373	210	7	characters	character	NOUN
bracis-28373	210	8	in	in	ADP
bracis-28373	210	9	the	the	DET
bracis-28373	210	10	emnist	emnist	NOUN
bracis-28373	210	11	dataset	dataset	NOUN
bracis-28373	210	12	.	.	PUNCT
bracis-28373	211	1	5	5	NUM
bracis-28373	211	2	results	result	NOUN
bracis-28373	211	3	in	in	ADP
bracis-28373	211	4	this	this	DET
bracis-28373	211	5	work	work	NOUN
bracis-28373	211	6	,	,	PUNCT
bracis-28373	211	7	in	in	ADP
bracis-28373	211	8	order	order	NOUN
bracis-28373	211	9	to	to	PART
bracis-28373	211	10	perform	perform	VERB
bracis-28373	211	11	a	a	DET
bracis-28373	211	12	quantitative	quantitative	ADJ
bracis-28373	211	13	comparison	comparison	NOUN
bracis-28373	211	14	,	,	PUNCT
bracis-28373	211	15	we	we	PRON
bracis-28373	211	16	compared	compare	VERB
bracis-28373	211	17	our	our	PRON
bracis-28373	211	18	approach	approach	NOUN
bracis-28373	211	19	in	in	ADP
bracis-28373	211	20	different	different	ADJ
bracis-28373	211	21	evaluation	evaluation	NOUN
bracis-28373	211	22	scenarios	scenario	NOUN
bracis-28373	211	23	.	.	PUNCT
bracis-28373	212	1	therefore	therefore	ADV
bracis-28373	212	2	,	,	PUNCT
bracis-28373	212	3	we	we	PRON
bracis-28373	212	4	considered	consider	VERB
bracis-28373	212	5	six	six	NUM
bracis-28373	212	6	experiments	experiment	NOUN
bracis-28373	212	7	with	with	ADP
bracis-28373	212	8	five	five	NUM
bracis-28373	212	9	techniques	technique	NOUN
bracis-28373	212	10	for	for	ADP
bracis-28373	212	11	mitigating	mitigate	VERB
bracis-28373	212	12	attacks	attack	NOUN
bracis-28373	212	13	in	in	ADP
bracis-28373	212	14	federated	federated	ADJ
bracis-28373	212	15	environments	environment	NOUN
bracis-28373	212	16	and	and	CCONJ
bracis-28373	212	17	fedavg	fedavg	NOUN
bracis-28373	212	18	aggregation	aggregation	NOUN
bracis-28373	212	19	.	.	PUNCT
bracis-28373	213	1	more	more	ADV
bracis-28373	213	2	specifically	specifically	ADV
bracis-28373	213	3	,	,	PUNCT
bracis-28373	213	4	we	we	PRON
bracis-28373	213	5	have	have	VERB
bracis-28373	213	6	the	the	DET
bracis-28373	213	7	following	following	NOUN
bracis-28373	213	8	:	:	PUNCT
bracis-28373	213	9	fedavg	fedavg	PROPN
bracis-28373	213	10	 	 	SPACE
bracis-28373	214	1	[	[	X
bracis-28373	214	2	15	15	NUM
bracis-28373	214	3	]	]	PUNCT
bracis-28373	214	4	is	be	AUX
bracis-28373	214	5	a	a	DET
bracis-28373	214	6	method	method	NOUN
bracis-28373	214	7	that	that	PRON
bracis-28373	214	8	uses	use	VERB
bracis-28373	214	9	the	the	DET
bracis-28373	214	10	weighted	weighted	ADJ
bracis-28373	214	11	average	average	NOUN
bracis-28373	214	12	of	of	ADP
bracis-28373	214	13	local	local	ADJ
bracis-28373	214	14	models	model	NOUN
bracis-28373	214	15	to	to	PART
bracis-28373	214	16	obtain	obtain	VERB
bracis-28373	214	17	a	a	DET
bracis-28373	214	18	more	more	ADV
bracis-28373	214	19	accurate	accurate	ADJ
bracis-28373	214	20	global	global	ADJ
bracis-28373	214	21	model	model	NOUN
bracis-28373	214	22	.	.	PUNCT
bracis-28373	215	1	the	the	DET
bracis-28373	215	2	fedavg	fedavg	PROPN
bracis-28373	215	3	aggregation	aggregation	NOUN
bracis-28373	215	4	is	be	AUX
bracis-28373	215	5	a	a	DET
bracis-28373	215	6	widespread	widespread	ADJ
bracis-28373	215	7	technique	technique	NOUN
bracis-28373	215	8	in	in	ADP
bracis-28373	215	9	fl	fl	NUM
bracis-28373	215	10	due	due	ADP
bracis-28373	215	11	to	to	ADP
bracis-28373	215	12	its	its	PRON
bracis-28373	215	13	effectiveness	effectiveness	NOUN
bracis-28373	215	14	and	and	CCONJ
bracis-28373	215	15	simplicity	simplicity	NOUN
bracis-28373	215	16	of	of	ADP
bracis-28373	215	17	implementation	implementation	NOUN
bracis-28373	215	18	.	.	PUNCT
bracis-28373	216	1	fedequal	fedequal	ADJ
bracis-28373	216	2	 	 	SPACE
bracis-28373	216	3	[	[	X
bracis-28373	216	4	5	5	NUM
bracis-28373	216	5	]	]	PUNCT
bracis-28373	216	6	equalizes	equalize	VERB
bracis-28373	216	7	the	the	DET
bracis-28373	216	8	weights	weight	NOUN
bracis-28373	216	9	of	of	ADP
bracis-28373	216	10	local	local	ADJ
bracis-28373	216	11	model	model	NOUN
bracis-28373	216	12	updates	update	NOUN
bracis-28373	216	13	in	in	ADP
bracis-28373	216	14	fl	fl	PROPN
bracis-28373	216	15	,	,	PUNCT
bracis-28373	216	16	allowing	allow	VERB
bracis-28373	216	17	most	most	ADJ
bracis-28373	216	18	benign	benign	ADJ
bracis-28373	216	19	models	model	NOUN
bracis-28373	216	20	to	to	ADP
bracis-28373	216	21	counterbalance	counterbalance	NOUN
bracis-28373	216	22	malicious	malicious	ADJ
bracis-28373	216	23	attackers	attacker	NOUN
bracis-28373	216	24	’	’	PART
bracis-28373	216	25	power	power	NOUN
bracis-28373	216	26	and	and	CCONJ
bracis-28373	216	27	avoid	avoid	VERB
bracis-28373	216	28	excluding	exclude	VERB
bracis-28373	216	29	local	local	ADJ
bracis-28373	216	30	models	model	NOUN
bracis-28373	216	31	.	.	PUNCT
bracis-28373	217	1	geometric	geometric	ADJ
bracis-28373	217	2	 	 	SPACE
bracis-28373	217	3	[	[	X
bracis-28373	217	4	16	16	NUM
bracis-28373	217	5	]	]	PUNCT
bracis-28373	217	6	uses	use	VERB
bracis-28373	217	7	the	the	DET
bracis-28373	217	8	geometric	geometric	ADJ
bracis-28373	217	9	mean	mean	NOUN
bracis-28373	217	10	of	of	ADP
bracis-28373	217	11	the	the	DET
bracis-28373	217	12	local	local	ADJ
bracis-28373	217	13	models	model	NOUN
bracis-28373	217	14	to	to	PART
bracis-28373	217	15	obtain	obtain	VERB
bracis-28373	217	16	a	a	DET
bracis-28373	217	17	global	global	ADJ
bracis-28373	217	18	model	model	NOUN
bracis-28373	217	19	that	that	PRON
bracis-28373	217	20	is	be	AUX
bracis-28373	217	21	more	more	ADV
bracis-28373	217	22	robust	robust	ADJ
bracis-28373	217	23	to	to	ADP
bracis-28373	217	24	outliers	outlier	NOUN
bracis-28373	217	25	.	.	PUNCT
bracis-28373	218	1	geometric	geometric	ADJ
bracis-28373	218	2	aggregation	aggregation	NOUN
bracis-28373	218	3	is	be	AUX
bracis-28373	218	4	an	an	DET
bracis-28373	218	5	alternative	alternative	ADJ
bracis-28373	218	6	technique	technique	NOUN
bracis-28373	218	7	to	to	ADP
bracis-28373	218	8	fedavg	fedavg	PROPN
bracis-28373	218	9	aggregation	aggregation	NOUN
bracis-28373	218	10	,	,	PUNCT
bracis-28373	218	11	which	which	PRON
bracis-28373	218	12	can	can	AUX
bracis-28373	218	13	be	be	AUX
bracis-28373	218	14	more	more	ADV
bracis-28373	218	15	effective	effective	ADJ
bracis-28373	218	16	in	in	ADP
bracis-28373	218	17	specific	specific	ADJ
bracis-28373	218	18	applications	application	NOUN
bracis-28373	218	19	.	.	PUNCT
bracis-28373	219	1	krum	krum	PROPN
bracis-28373	219	2	 	 	SPACE
bracis-28373	220	1	[	[	X
bracis-28373	220	2	4	4	X
bracis-28373	220	3	]	]	PUNCT
bracis-28373	220	4	is	be	AUX
bracis-28373	220	5	a	a	DET
bracis-28373	220	6	robust	robust	ADJ
bracis-28373	220	7	aggregation	aggregation	NOUN
bracis-28373	220	8	rule	rule	NOUN
bracis-28373	220	9	that	that	PRON
bracis-28373	220	10	uses	use	VERB
bracis-28373	220	11	a	a	DET
bracis-28373	220	12	euclidean	euclidean	ADJ
bracis-28373	220	13	distance	distance	NOUN
bracis-28373	220	14	approach	approach	NOUN
bracis-28373	220	15	to	to	PART
bracis-28373	220	16	select	select	VERB
bracis-28373	220	17	similar	similar	ADJ
bracis-28373	220	18	model	model	NOUN
bracis-28373	220	19	updates	update	NOUN
bracis-28373	220	20	.	.	PUNCT
bracis-28373	221	1	this	this	DET
bracis-28373	221	2	method	method	NOUN
bracis-28373	221	3	calculates	calculate	VERB
bracis-28373	221	4	the	the	DET
bracis-28373	221	5	sum	sum	NOUN
bracis-28373	221	6	of	of	ADP
bracis-28373	221	7	squared	squared	ADJ
bracis-28373	221	8	distances	distance	NOUN
bracis-28373	221	9	between	between	ADP
bracis-28373	221	10	local	local	ADJ
bracis-28373	221	11	model	model	NOUN
bracis-28373	221	12	updates	update	NOUN
bracis-28373	221	13	and	and	CCONJ
bracis-28373	221	14	then	then	ADV
bracis-28373	221	15	selects	select	VERB
bracis-28373	221	16	the	the	DET
bracis-28373	221	17	model	model	NOUN
bracis-28373	221	18	update	update	NOUN
bracis-28373	221	19	with	with	ADP
bracis-28373	221	20	the	the	DET
bracis-28373	221	21	lowest	low	ADJ
bracis-28373	221	22	sum	sum	NOUN
bracis-28373	221	23	to	to	PART
bracis-28373	221	24	update	update	VERB
bracis-28373	221	25	the	the	DET
bracis-28373	221	26	parameters	parameter	NOUN
bracis-28373	221	27	of	of	ADP
bracis-28373	221	28	the	the	DET
bracis-28373	221	29	global	global	ADJ
bracis-28373	221	30	model	model	NOUN
bracis-28373	221	31	.	.	PUNCT
bracis-28373	222	1	norm	norm	NOUN
bracis-28373	222	2	 	 	SPACE
bracis-28373	223	1	[	[	X
bracis-28373	223	2	20	20	NUM
bracis-28373	223	3	]	]	PUNCT
bracis-28373	223	4	consists	consist	VERB
bracis-28373	223	5	of	of	ADP
bracis-28373	223	6	calculating	calculate	VERB
bracis-28373	223	7	a	a	DET
bracis-28373	223	8	normalization	normalization	NOUN
bracis-28373	223	9	constant	constant	ADJ
bracis-28373	223	10	for	for	ADP
bracis-28373	223	11	model	model	NOUN
bracis-28373	223	12	updates	update	NOUN
bracis-28373	223	13	by	by	ADP
bracis-28373	223	14	clients	client	NOUN
bracis-28373	223	15	to	to	PART
bracis-28373	223	16	normalize	normalize	VERB
bracis-28373	223	17	the	the	DET
bracis-28373	223	18	contribution	contribution	NOUN
bracis-28373	223	19	of	of	ADP
bracis-28373	223	20	any	any	DET
bracis-28373	223	21	individual	individual	ADJ
bracis-28373	223	22	participant	participant	NOUN
bracis-28373	223	23	.	.	PUNCT
bracis-28373	224	1	so	so	ADV
bracis-28373	224	2	,	,	PUNCT
bracis-28373	224	3	all	all	DET
bracis-28373	224	4	model	model	NOUN
bracis-28373	224	5	updates	update	NOUN
bracis-28373	224	6	are	be	AUX
bracis-28373	224	7	averaged	average	VERB
bracis-28373	224	8	to	to	PART
bracis-28373	224	9	update	update	VERB
bracis-28373	224	10	the	the	DET
bracis-28373	224	11	joint	joint	ADJ
bracis-28373	224	12	global	global	ADJ
bracis-28373	224	13	model	model	NOUN
bracis-28373	224	14	.	.	PUNCT
bracis-28373	225	1	trimmed	trim	VERB
bracis-28373	225	2	 	 	SPACE
bracis-28373	226	1	[	[	X
bracis-28373	226	2	23	23	NUM
bracis-28373	226	3	]	]	PUNCT
bracis-28373	226	4	can	can	AUX
bracis-28373	226	5	be	be	AUX
bracis-28373	226	6	defined	define	VERB
bracis-28373	226	7	as	as	ADP
bracis-28373	226	8	the	the	DET
bracis-28373	226	9	average	average	NOUN
bracis-28373	226	10	of	of	ADP
bracis-28373	226	11	the	the	DET
bracis-28373	226	12	local	local	ADJ
bracis-28373	226	13	models	model	NOUN
bracis-28373	226	14	but	but	CCONJ
bracis-28373	226	15	removes	remove	VERB
bracis-28373	226	16	a	a	DET
bracis-28373	226	17	proportion	proportion	NOUN
bracis-28373	226	18	of	of	ADP
bracis-28373	226	19	the	the	DET
bracis-28373	226	20	local	local	ADJ
bracis-28373	226	21	models	model	NOUN
bracis-28373	226	22	,	,	PUNCT
bracis-28373	226	23	including	include	VERB
bracis-28373	226	24	outliers	outlier	NOUN
bracis-28373	226	25	,	,	PUNCT
bracis-28373	226	26	that	that	PRON
bracis-28373	226	27	may	may	AUX
bracis-28373	226	28	negatively	negatively	ADV
bracis-28373	226	29	affect	affect	VERB
bracis-28373	226	30	the	the	DET
bracis-28373	226	31	aggregation	aggregation	NOUN
bracis-28373	226	32	.	.	PUNCT
bracis-28373	227	1	trimmed	trim	VERB
bracis-28373	227	2	aggregation	aggregation	NOUN
bracis-28373	227	3	is	be	AUX
bracis-28373	227	4	a	a	DET
bracis-28373	227	5	technique	technique	NOUN
bracis-28373	227	6	that	that	PRON
bracis-28373	227	7	can	can	AUX
bracis-28373	227	8	improve	improve	VERB
bracis-28373	227	9	the	the	DET
bracis-28373	227	10	effectiveness	effectiveness	NOUN
bracis-28373	227	11	of	of	ADP
bracis-28373	227	12	model	model	NOUN
bracis-28373	227	13	aggregation	aggregation	NOUN
bracis-28373	227	14	in	in	ADP
bracis-28373	227	15	fl	fl	PROPN
bracis-28373	227	16	systems	system	NOUN
bracis-28373	227	17	,	,	PUNCT
bracis-28373	227	18	especially	especially	ADV
bracis-28373	227	19	when	when	SCONJ
bracis-28373	227	20	there	there	PRON
bracis-28373	227	21	is	be	VERB
bracis-28373	227	22	a	a	DET
bracis-28373	227	23	significant	significant	ADJ
bracis-28373	227	24	variation	variation	NOUN
bracis-28373	227	25	in	in	ADP
bracis-28373	227	26	the	the	DET
bracis-28373	227	27	local	local	ADJ
bracis-28373	227	28	data	datum	NOUN
bracis-28373	227	29	.	.	PUNCT
bracis-28373	228	1	on	on	ADP
bracis-28373	228	2	the	the	DET
bracis-28373	228	3	other	other	ADJ
bracis-28373	228	4	hand	hand	NOUN
bracis-28373	228	5	,	,	PUNCT
bracis-28373	228	6	besides	besides	SCONJ
bracis-28373	228	7	our	our	PRON
bracis-28373	228	8	proposed	propose	VERB
bracis-28373	228	9	attack	attack	NOUN
bracis-28373	228	10	,	,	PUNCT
bracis-28373	228	11	we	we	PRON
bracis-28373	228	12	evaluated	evaluate	VERB
bracis-28373	228	13	our	our	PRON
bracis-28373	228	14	federation	federation	NOUN
bracis-28373	228	15	using	use	VERB
bracis-28373	228	16	four	four	NUM
bracis-28373	228	17	attack	attack	NOUN
bracis-28373	228	18	proposals	proposal	NOUN
bracis-28373	228	19	in	in	ADP
bracis-28373	228	20	federated	federated	ADJ
bracis-28373	228	21	environments	environment	NOUN
bracis-28373	228	22	in	in	ADP
bracis-28373	228	23	addition	addition	NOUN
bracis-28373	228	24	to	to	ADP
bracis-28373	228	25	the	the	DET
bracis-28373	228	26	standard	standard	ADJ
bracis-28373	228	27	proposal	proposal	NOUN
bracis-28373	228	28	without	without	ADP
bracis-28373	228	29	malicious	malicious	ADJ
bracis-28373	228	30	clients	client	NOUN
bracis-28373	228	31	for	for	ADP
bracis-28373	228	32	each	each	PRON
bracis-28373	228	33	of	of	ADP
bracis-28373	228	34	the	the	DET
bracis-28373	228	35	six	six	NUM
bracis-28373	228	36	experiments	experiment	NOUN
bracis-28373	228	37	:	:	PUNCT
bracis-28373	228	38	none	none	NOUN
bracis-28373	228	39	:	:	PUNCT
bracis-28373	228	40	approach	approach	NOUN
bracis-28373	228	41	without	without	ADP
bracis-28373	228	42	any	any	DET
bracis-28373	228	43	malicious	malicious	ADJ
bracis-28373	228	44	client	client	NOUN
bracis-28373	228	45	.	.	PUNCT
bracis-28373	229	1	fedattack	fedattack	NOUN
bracis-28373	229	2	 	 	SPACE
bracis-28373	230	1	[	[	X
bracis-28373	230	2	22	22	NUM
bracis-28373	230	3	]	]	PUNCT
bracis-28373	230	4	:	:	PUNCT
bracis-28373	230	5	uses	use	VERB
bracis-28373	230	6	a	a	DET
bracis-28373	230	7	contrastive	contrastive	ADJ
bracis-28373	230	8	approach	approach	NOUN
bracis-28373	230	9	to	to	ADP
bracis-28373	230	10	group	group	NOUN
bracis-28373	230	11	corrupted	corrupt	VERB
bracis-28373	230	12	samples	sample	NOUN
bracis-28373	230	13	into	into	ADP
bracis-28373	230	14	similar	similar	ADJ
bracis-28373	230	15	regions	region	NOUN
bracis-28373	230	16	.	.	PUNCT
bracis-28373	231	1	the	the	DET
bracis-28373	231	2	authors	author	NOUN
bracis-28373	231	3	propose	propose	VERB
bracis-28373	231	4	to	to	PART
bracis-28373	231	5	use	use	VERB
bracis-28373	231	6	globally	globally	ADV
bracis-28373	231	7	hardest	hard	ADV
bracis-28373	231	8	sampling	sample	VERB
bracis-28373	231	9	as	as	ADP
bracis-28373	231	10	a	a	DET
bracis-28373	231	11	poisoning	poisoning	NOUN
bracis-28373	231	12	technique	technique	NOUN
bracis-28373	231	13	.	.	PUNCT
bracis-28373	232	1	however	however	ADV
bracis-28373	232	2	,	,	PUNCT
bracis-28373	232	3	the	the	DET
bracis-28373	232	4	technique	technique	NOUN
bracis-28373	232	5	involves	involve	VERB
bracis-28373	232	6	malicious	malicious	ADJ
bracis-28373	232	7	clients	client	NOUN
bracis-28373	232	8	using	use	VERB
bracis-28373	232	9	their	their	PRON
bracis-28373	232	10	local	local	ADJ
bracis-28373	232	11	user	user	NOUN
bracis-28373	232	12	embedding	embed	VERB
bracis-28373	232	13	to	to	PART
bracis-28373	232	14	retrieve	retrieve	VERB
bracis-28373	232	15	globally	globally	ADV
bracis-28373	232	16	hardest	hard	ADJ
bracis-28373	232	17	negative	negative	ADJ
bracis-28373	232	18	samples	sample	NOUN
bracis-28373	232	19	and	and	CCONJ
bracis-28373	232	20	pseudo	pseudo	NOUN
bracis-28373	232	21	“	"	PUNCT
bracis-28373	232	22	hardest	hard	ADJ
bracis-28373	232	23	positive	positive	ADJ
bracis-28373	232	24	samples	sample	NOUN
bracis-28373	232	25	”	"	PUNCT
bracis-28373	232	26	to	to	PART
bracis-28373	232	27	increase	increase	VERB
bracis-28373	232	28	the	the	DET
bracis-28373	232	29	difficulty	difficulty	NOUN
bracis-28373	232	30	of	of	ADP
bracis-28373	232	31	model	model	NOUN
bracis-28373	232	32	training	training	NOUN
bracis-28373	232	33	.	.	PUNCT
bracis-28373	233	1	label	label	NOUN
bracis-28373	233	2	 	 	SPACE
bracis-28373	234	1	[	[	X
bracis-28373	234	2	22	22	NUM
bracis-28373	234	3	]	]	X
bracis-28373	234	4	:	:	PUNCT
bracis-28373	234	5	label	label	NOUN
bracis-28373	234	6	flipping	flip	VERB
bracis-28373	234	7	attack	attack	NOUN
bracis-28373	234	8	approach	approach	NOUN
bracis-28373	234	9	that	that	PRON
bracis-28373	234	10	randomly	randomly	ADV
bracis-28373	234	11	flips	flip	VERB
bracis-28373	234	12	the	the	DET
bracis-28373	234	13	labels	label	NOUN
bracis-28373	234	14	of	of	ADP
bracis-28373	234	15	the	the	DET
bracis-28373	234	16	malicious	malicious	ADJ
bracis-28373	234	17	client	client	NOUN
bracis-28373	234	18	’s	’s	PART
bracis-28373	234	19	dataset	dataset	NOUN
bracis-28373	234	20	and	and	CCONJ
bracis-28373	234	21	trains	train	NOUN
bracis-28373	234	22	on	on	ADP
bracis-28373	234	23	the	the	DET
bracis-28373	234	24	contaminated	contaminate	VERB
bracis-28373	234	25	dataset	dataset	NOUN
bracis-28373	234	26	using	use	VERB
bracis-28373	234	27	cross	cross	ADJ
bracis-28373	234	28	-	-	ADJ
bracis-28373	234	29	entropy	entropy	ADJ
bracis-28373	234	30	loss	loss	NOUN
bracis-28373	234	31	.	.	PUNCT
bracis-28373	235	1	stat	stat	NOUN
bracis-28373	235	2	-	-	PUNCT
bracis-28373	235	3	opt	opt	VERB
bracis-28373	235	4	 	 	SPACE
bracis-28373	236	1	[	[	X
bracis-28373	236	2	7	7	NUM
bracis-28373	236	3	]	]	NOUN
bracis-28373	236	4	:	:	PUNCT
bracis-28373	236	5	attack	attack	NOUN
bracis-28373	236	6	that	that	PRON
bracis-28373	236	7	consists	consist	VERB
bracis-28373	236	8	of	of	ADP
bracis-28373	236	9	adding	add	VERB
bracis-28373	236	10	constant	constant	ADJ
bracis-28373	236	11	noise	noise	NOUN
bracis-28373	236	12	with	with	ADP
bracis-28373	236	13	opposite	opposite	ADJ
bracis-28373	236	14	directions	direction	NOUN
bracis-28373	236	15	to	to	ADP
bracis-28373	236	16	the	the	DET
bracis-28373	236	17	average	average	NOUN
bracis-28373	236	18	of	of	ADP
bracis-28373	236	19	benign	benign	ADJ
bracis-28373	236	20	gradients	gradient	NOUN
bracis-28373	236	21	.	.	PUNCT
bracis-28373	237	1	note	note	VERB
bracis-28373	237	2	que	que	PROPN
bracis-28373	237	3	the	the	DET
bracis-28373	237	4	malicious	malicious	ADJ
bracis-28373	237	5	clients	client	NOUN
bracis-28373	237	6	in	in	ADP
bracis-28373	237	7	fedattack	fedattack	NOUN
bracis-28373	237	8	,	,	PUNCT
bracis-28373	237	9	label	label	NOUN
bracis-28373	237	10	,	,	PUNCT
bracis-28373	237	11	and	and	CCONJ
bracis-28373	237	12	our	our	PRON
bracis-28373	237	13	proposal	proposal	NOUN
bracis-28373	237	14	only	only	ADV
bracis-28373	237	15	modify	modify	VERB
bracis-28373	237	16	the	the	DET
bracis-28373	237	17	input	input	NOUN
bracis-28373	237	18	samples	sample	NOUN
bracis-28373	237	19	and	and	CCONJ
bracis-28373	237	20	their	their	PRON
bracis-28373	237	21	labels	label	NOUN
bracis-28373	237	22	.	.	PUNCT
bracis-28373	238	1	at	at	ADP
bracis-28373	238	2	the	the	DET
bracis-28373	238	3	same	same	ADJ
bracis-28373	238	4	time	time	NOUN
bracis-28373	238	5	,	,	PUNCT
bracis-28373	238	6	the	the	DET
bracis-28373	238	7	model	model	NOUN
bracis-28373	238	8	gradients	gradient	NOUN
bracis-28373	238	9	are	be	AUX
bracis-28373	238	10	directly	directly	ADV
bracis-28373	238	11	computed	compute	VERB
bracis-28373	238	12	on	on	ADP
bracis-28373	238	13	these	these	DET
bracis-28373	238	14	samples	sample	NOUN
bracis-28373	238	15	without	without	ADP
bracis-28373	238	16	further	further	ADJ
bracis-28373	238	17	manipulation	manipulation	NOUN
bracis-28373	238	18	.	.	PUNCT
bracis-28373	239	1	finally	finally	ADV
bracis-28373	239	2	,	,	PUNCT
bracis-28373	239	3	table	table	NOUN
bracis-28373	239	4	 	 	SPACE
bracis-28373	239	5	1	1	NUM
bracis-28373	239	6	displays	display	VERB
bracis-28373	239	7	the	the	DET
bracis-28373	239	8	performance	performance	NOUN
bracis-28373	239	9	of	of	ADP
bracis-28373	239	10	the	the	DET
bracis-28373	239	11	described	describe	VERB
bracis-28373	239	12	defense	defense	NOUN
bracis-28373	239	13	mechanisms	mechanism	NOUN
bracis-28373	239	14	against	against	ADP
bracis-28373	239	15	various	various	ADJ
bracis-28373	239	16	attacks	attack	NOUN
bracis-28373	239	17	in	in	ADP
bracis-28373	239	18	federated	federated	ADJ
bracis-28373	239	19	learning	learning	NOUN
bracis-28373	239	20	.	.	PUNCT
bracis-28373	240	1	the	the	DET
bracis-28373	240	2	performance	performance	NOUN
bracis-28373	240	3	is	be	AUX
bracis-28373	240	4	assessed	assess	VERB
bracis-28373	240	5	based	base	VERB
bracis-28373	240	6	on	on	ADP
bracis-28373	240	7	accuracy	accuracy	NOUN
bracis-28373	240	8	,	,	PUNCT
bracis-28373	240	9	precision	precision	NOUN
bracis-28373	240	10	,	,	PUNCT
bracis-28373	240	11	recall	recall	NOUN
bracis-28373	240	12	,	,	PUNCT
bracis-28373	240	13	and	and	CCONJ
bracis-28373	240	14	f1	f1	NOUN
bracis-28373	240	15	-	-	PUNCT
bracis-28373	240	16	score	score	NOUN
bracis-28373	240	17	.	.	PUNCT
bracis-28373	241	1	the	the	DET
bracis-28373	241	2	best	good	ADJ
bracis-28373	241	3	performance	performance	NOUN
bracis-28373	241	4	is	be	AUX
bracis-28373	241	5	highlighted	highlight	VERB
bracis-28373	241	6	in	in	ADP
bracis-28373	241	7	bold	bold	ADJ
bracis-28373	241	8	in	in	ADP
bracis-28373	241	9	each	each	DET
bracis-28373	241	10	category	category	NOUN
bracis-28373	241	11	.	.	PUNCT
bracis-28373	242	1	it	it	PRON
bracis-28373	242	2	is	be	AUX
bracis-28373	242	3	worth	worth	ADJ
bracis-28373	242	4	noting	note	VERB
bracis-28373	242	5	that	that	SCONJ
bracis-28373	242	6	the	the	DET
bracis-28373	242	7	proposed	propose	VERB
bracis-28373	242	8	attack	attack	NOUN
bracis-28373	242	9	model	model	NOUN
bracis-28373	242	10	aims	aim	VERB
bracis-28373	242	11	to	to	PART
bracis-28373	242	12	maximize	maximize	VERB
bracis-28373	242	13	its	its	PRON
bracis-28373	242	14	success	success	NOUN
bracis-28373	242	15	rate	rate	NOUN
bracis-28373	242	16	.	.	PUNCT
bracis-28373	243	1	thus	thus	ADV
bracis-28373	243	2	a	a	DET
bracis-28373	243	3	lower	low	ADJ
bracis-28373	243	4	performance	performance	NOUN
bracis-28373	243	5	is	be	AUX
bracis-28373	243	6	better	well	ADJ
bracis-28373	243	7	in	in	ADP
bracis-28373	243	8	comparison	comparison	NOUN
bracis-28373	243	9	to	to	ADP
bracis-28373	243	10	other	other	ADJ
bracis-28373	243	11	defense	defense	NOUN
bracis-28373	243	12	proposals	proposal	NOUN
bracis-28373	243	13	.	.	PUNCT
bracis-28373	244	1	table	table	NOUN
bracis-28373	244	2	1	1	NUM
bracis-28373	244	3	.	.	PUNCT
bracis-28373	245	1	the	the	DET
bracis-28373	245	2	table	table	NOUN
bracis-28373	245	3	shows	show	VERB
bracis-28373	245	4	the	the	DET
bracis-28373	245	5	performance	performance	NOUN
bracis-28373	245	6	of	of	ADP
bracis-28373	245	7	various	various	ADJ
bracis-28373	245	8	defense	defense	NOUN
bracis-28373	245	9	mechanisms	mechanism	NOUN
bracis-28373	245	10	against	against	ADP
bracis-28373	245	11	different	different	ADJ
bracis-28373	245	12	attack	attack	NOUN
bracis-28373	245	13	proposals	proposal	NOUN
bracis-28373	245	14	in	in	ADP
bracis-28373	245	15	a	a	DET
bracis-28373	245	16	federated	federated	ADJ
bracis-28373	245	17	learning	learning	NOUN
bracis-28373	245	18	setting	setting	NOUN
bracis-28373	245	19	.	.	PUNCT
bracis-28373	246	1	the	the	DET
bracis-28373	246	2	evaluation	evaluation	NOUN
bracis-28373	246	3	metrics	metric	NOUN
bracis-28373	246	4	include	include	VERB
bracis-28373	246	5	accuracy	accuracy	NOUN
bracis-28373	246	6	,	,	PUNCT
bracis-28373	246	7	precision	precision	NOUN
bracis-28373	246	8	,	,	PUNCT
bracis-28373	246	9	recall	recall	NOUN
bracis-28373	246	10	,	,	PUNCT
bracis-28373	246	11	and	and	CCONJ
bracis-28373	246	12	f1	f1	NOUN
bracis-28373	246	13	-	-	PUNCT
bracis-28373	246	14	score	score	NOUN
bracis-28373	246	15	.	.	PUNCT
bracis-28373	247	1	the	the	DET
bracis-28373	247	2	best	good	ADJ
bracis-28373	247	3	values	value	NOUN
bracis-28373	247	4	were	be	AUX
bracis-28373	247	5	shown	show	VERB
bracis-28373	247	6	in	in	ADP
bracis-28373	247	7	bold	bold	ADJ
bracis-28373	247	8	(	(	PUNCT
bracis-28373	247	9	lower	low	ADJ
bracis-28373	247	10	is	be	AUX
bracis-28373	247	11	better).full	better).full	NOUN
bracis-28373	247	12	size	size	NOUN
bracis-28373	247	13	table	table	NOUN
bracis-28373	247	14	initially	initially	ADV
bracis-28373	247	15	,	,	PUNCT
bracis-28373	247	16	we	we	PRON
bracis-28373	247	17	verified	verify	VERB
bracis-28373	247	18	that	that	SCONJ
bracis-28373	247	19	the	the	DET
bracis-28373	247	20	“	"	PUNCT
bracis-28373	247	21	label	label	NOUN
bracis-28373	247	22	”	"	PUNCT
bracis-28373	247	23	approach	approach	NOUN
bracis-28373	247	24	is	be	AUX
bracis-28373	247	25	a	a	DET
bracis-28373	247	26	simplified	simplified	ADJ
bracis-28373	247	27	version	version	NOUN
bracis-28373	247	28	of	of	ADP
bracis-28373	247	29	our	our	PRON
bracis-28373	247	30	proposed	propose	VERB
bracis-28373	247	31	attack	attack	NOUN
bracis-28373	247	32	,	,	PUNCT
bracis-28373	247	33	using	use	VERB
bracis-28373	247	34	the	the	DET
bracis-28373	247	35	usual	usual	ADJ
bracis-28373	247	36	cross	cross	ADJ
bracis-28373	247	37	-	-	ADJ
bracis-28373	247	38	entropy	entropy	ADJ
bracis-28373	247	39	loss	loss	NOUN
bracis-28373	247	40	in	in	ADP
bracis-28373	247	41	a	a	DET
bracis-28373	247	42	label	label	NOUN
bracis-28373	247	43	attack	attack	NOUN
bracis-28373	247	44	.	.	PUNCT
bracis-28373	248	1	in	in	ADP
bracis-28373	248	2	contrast	contrast	NOUN
bracis-28373	248	3	,	,	PUNCT
bracis-28373	248	4	our	our	PRON
bracis-28373	248	5	proposal	proposal	NOUN
bracis-28373	248	6	uses	use	VERB
bracis-28373	248	7	a	a	DET
bracis-28373	248	8	bayesian	bayesian	NOUN
bracis-28373	248	9	neural	neural	ADJ
bracis-28373	248	10	network	network	NOUN
bracis-28373	248	11	trained	train	VERB
bracis-28373	248	12	with	with	ADP
bracis-28373	248	13	marginal	marginal	ADJ
bracis-28373	248	14	likelihood	likelihood	NOUN
bracis-28373	248	15	.	.	PUNCT
bracis-28373	249	1	the	the	DET
bracis-28373	249	2	results	result	NOUN
bracis-28373	249	3	show	show	VERB
bracis-28373	249	4	that	that	SCONJ
bracis-28373	249	5	our	our	PRON
bracis-28373	249	6	attack	attack	NOUN
bracis-28373	249	7	proposal	proposal	NOUN
bracis-28373	249	8	is	be	AUX
bracis-28373	249	9	more	more	ADV
bracis-28373	249	10	effective	effective	ADJ
bracis-28373	249	11	than	than	ADP
bracis-28373	249	12	the	the	DET
bracis-28373	249	13	label	label	NOUN
bracis-28373	249	14	approach	approach	NOUN
bracis-28373	249	15	.	.	PUNCT
bracis-28373	250	1	in	in	ADP
bracis-28373	250	2	all	all	DET
bracis-28373	250	3	defense	defense	NOUN
bracis-28373	250	4	scenarios	scenario	NOUN
bracis-28373	250	5	,	,	PUNCT
bracis-28373	250	6	our	our	PRON
bracis-28373	250	7	proposal	proposal	NOUN
bracis-28373	250	8	had	have	VERB
bracis-28373	250	9	a	a	DET
bracis-28373	250	10	lower	low	ADJ
bracis-28373	250	11	performance	performance	NOUN
bracis-28373	250	12	,	,	PUNCT
bracis-28373	250	13	i.e.	i.e.	X
bracis-28373	250	14	,	,	PUNCT
bracis-28373	250	15	our	our	PRON
bracis-28373	250	16	proposal	proposal	NOUN
bracis-28373	250	17	was	be	AUX
bracis-28373	250	18	able	able	ADJ
bracis-28373	250	19	to	to	PART
bracis-28373	250	20	reduce	reduce	VERB
bracis-28373	250	21	accuracy	accuracy	NOUN
bracis-28373	250	22	,	,	PUNCT
bracis-28373	250	23	precision	precision	NOUN
bracis-28373	250	24	,	,	PUNCT
bracis-28373	250	25	recall	recall	NOUN
bracis-28373	250	26	,	,	PUNCT
bracis-28373	250	27	and	and	CCONJ
bracis-28373	250	28	f1	f1	NOUN
bracis-28373	250	29	-	-	PUNCT
bracis-28373	250	30	score	score	NOUN
bracis-28373	250	31	significantly	significantly	ADV
bracis-28373	250	32	.	.	PUNCT
bracis-28373	251	1	the	the	DET
bracis-28373	251	2	results	result	NOUN
bracis-28373	251	3	also	also	ADV
bracis-28373	251	4	show	show	VERB
bracis-28373	251	5	that	that	SCONJ
bracis-28373	251	6	the	the	DET
bracis-28373	251	7	performance	performance	NOUN
bracis-28373	251	8	of	of	ADP
bracis-28373	251	9	defense	defense	NOUN
bracis-28373	251	10	mechanisms	mechanism	NOUN
bracis-28373	251	11	varies	vary	VERB
bracis-28373	251	12	according	accord	VERB
bracis-28373	251	13	to	to	ADP
bracis-28373	251	14	the	the	DET
bracis-28373	251	15	attack	attack	NOUN
bracis-28373	251	16	proposal	proposal	NOUN
bracis-28373	251	17	and	and	CCONJ
bracis-28373	251	18	the	the	DET
bracis-28373	251	19	type	type	NOUN
bracis-28373	251	20	of	of	ADP
bracis-28373	251	21	defense	defense	NOUN
bracis-28373	251	22	used	use	VERB
bracis-28373	251	23	.	.	PUNCT
bracis-28373	252	1	for	for	ADP
bracis-28373	252	2	example	example	NOUN
bracis-28373	252	3	,	,	PUNCT
bracis-28373	252	4	the	the	DET
bracis-28373	252	5	“	"	PUNCT
bracis-28373	252	6	fedavg	fedavg	PROPN
bracis-28373	252	7	”	"	PUNCT
bracis-28373	252	8	defense	defense	NOUN
bracis-28373	252	9	was	be	AUX
bracis-28373	252	10	less	less	ADV
bracis-28373	252	11	effective	effective	ADJ
bracis-28373	252	12	against	against	ADP
bracis-28373	252	13	label	label	NOUN
bracis-28373	252	14	attacks	attack	NOUN
bracis-28373	252	15	than	than	ADP
bracis-28373	252	16	other	other	ADJ
bracis-28373	252	17	defense	defense	NOUN
bracis-28373	252	18	proposals	proposal	NOUN
bracis-28373	252	19	.	.	PUNCT
bracis-28373	253	1	in	in	ADP
bracis-28373	253	2	general	general	ADJ
bracis-28373	253	3	,	,	PUNCT
bracis-28373	253	4	our	our	PRON
bracis-28373	253	5	attack	attack	NOUN
bracis-28373	253	6	proposal	proposal	NOUN
bracis-28373	253	7	proved	prove	VERB
bracis-28373	253	8	more	more	ADV
bracis-28373	253	9	effective	effective	ADJ
bracis-28373	253	10	in	in	ADP
bracis-28373	253	11	all	all	DET
bracis-28373	253	12	scenarios	scenario	NOUN
bracis-28373	253	13	,	,	PUNCT
bracis-28373	253	14	regardless	regardless	ADV
bracis-28373	253	15	of	of	ADP
bracis-28373	253	16	the	the	DET
bracis-28373	253	17	type	type	NOUN
bracis-28373	253	18	of	of	ADP
bracis-28373	253	19	defense	defense	NOUN
bracis-28373	253	20	used	use	VERB
bracis-28373	253	21	compared	compare	VERB
bracis-28373	253	22	to	to	ADP
bracis-28373	253	23	the	the	DET
bracis-28373	253	24	label	label	NOUN
bracis-28373	253	25	attack	attack	NOUN
bracis-28373	253	26	approach	approach	NOUN
bracis-28373	253	27	.	.	PUNCT
bracis-28373	254	1	for	for	ADP
bracis-28373	254	2	the	the	DET
bracis-28373	254	3	other	other	ADJ
bracis-28373	254	4	approaches	approach	NOUN
bracis-28373	254	5	,	,	PUNCT
bracis-28373	254	6	compared	compare	VERB
bracis-28373	254	7	to	to	ADP
bracis-28373	254	8	the	the	DET
bracis-28373	254	9	fedavg	fedavg	PROPN
bracis-28373	254	10	defense	defense	NOUN
bracis-28373	254	11	proposal	proposal	NOUN
bracis-28373	254	12	,	,	PUNCT
bracis-28373	254	13	the	the	DET
bracis-28373	254	14	results	result	NOUN
bracis-28373	254	15	show	show	VERB
bracis-28373	254	16	that	that	SCONJ
bracis-28373	254	17	the	the	DET
bracis-28373	254	18	stat	stat	NOUN
bracis-28373	254	19	-	-	PUNCT
bracis-28373	254	20	opt	opt	NOUN
bracis-28373	254	21	proposal	proposal	NOUN
bracis-28373	254	22	had	have	VERB
bracis-28373	254	23	the	the	DET
bracis-28373	254	24	best	good	ADJ
bracis-28373	254	25	attack	attack	NOUN
bracis-28373	254	26	performance	performance	NOUN
bracis-28373	254	27	,	,	PUNCT
bracis-28373	254	28	with	with	ADP
bracis-28373	254	29	an	an	DET
bracis-28373	254	30	accuracy	accuracy	NOUN
bracis-28373	254	31	of	of	ADP
bracis-28373	254	32	0.584	0.584	NUM
bracis-28373	254	33	,	,	PUNCT
bracis-28373	254	34	precision	precision	NOUN
bracis-28373	254	35	of	of	ADP
bracis-28373	254	36	0.593	0.593	NUM
bracis-28373	254	37	,	,	PUNCT
bracis-28373	254	38	recall	recall	NOUN
bracis-28373	254	39	of	of	ADP
bracis-28373	254	40	0.581	0.581	NUM
bracis-28373	254	41	,	,	PUNCT
bracis-28373	254	42	and	and	CCONJ
bracis-28373	254	43	f1	f1	NOUN
bracis-28373	254	44	-	-	PUNCT
bracis-28373	254	45	score	score	NOUN
bracis-28373	254	46	of	of	ADP
bracis-28373	254	47	0.587	0.587	NUM
bracis-28373	254	48	.	.	PUNCT
bracis-28373	255	1	in	in	ADP
bracis-28373	255	2	the	the	DET
bracis-28373	255	3	second	second	ADJ
bracis-28373	255	4	place	place	NOUN
bracis-28373	255	5	,	,	PUNCT
bracis-28373	255	6	we	we	PRON
bracis-28373	255	7	observed	observe	VERB
bracis-28373	255	8	that	that	SCONJ
bracis-28373	255	9	our	our	PRON
bracis-28373	255	10	proposal	proposal	NOUN
bracis-28373	255	11	had	have	VERB
bracis-28373	255	12	slightly	slightly	ADV
bracis-28373	255	13	better	well	ADJ
bracis-28373	255	14	performance	performance	NOUN
bracis-28373	255	15	than	than	ADP
bracis-28373	255	16	the	the	DET
bracis-28373	255	17	“	"	PUNCT
bracis-28373	255	18	fedattack	fedattack	NOUN
bracis-28373	255	19	”	"	PUNCT
bracis-28373	255	20	model	model	NOUN
bracis-28373	255	21	,	,	PUNCT
bracis-28373	255	22	with	with	ADP
bracis-28373	255	23	an	an	DET
bracis-28373	255	24	accuracy	accuracy	NOUN
bracis-28373	255	25	of	of	ADP
bracis-28373	255	26	0.603	0.603	NUM
bracis-28373	255	27	,	,	PUNCT
bracis-28373	255	28	precision	precision	NOUN
bracis-28373	255	29	of	of	ADP
bracis-28373	255	30	0.632	0.632	NUM
bracis-28373	255	31	,	,	PUNCT
bracis-28373	255	32	recall	recall	NOUN
bracis-28373	255	33	of	of	ADP
bracis-28373	255	34	0.607	0.607	NUM
bracis-28373	255	35	,	,	PUNCT
bracis-28373	255	36	and	and	CCONJ
bracis-28373	255	37	f1	f1	NOUN
bracis-28373	255	38	-	-	PUNCT
bracis-28373	255	39	score	score	NOUN
bracis-28373	255	40	of	of	ADP
bracis-28373	255	41	0.595	0.595	NUM
bracis-28373	255	42	.	.	PUNCT
bracis-28373	256	1	a	a	DET
bracis-28373	256	2	similar	similar	ADJ
bracis-28373	256	3	conclusion	conclusion	NOUN
bracis-28373	256	4	was	be	AUX
bracis-28373	256	5	observed	observe	VERB
bracis-28373	256	6	for	for	ADP
bracis-28373	256	7	the	the	DET
bracis-28373	256	8	fedequal	fedequal	ADJ
bracis-28373	256	9	defense	defense	NOUN
bracis-28373	256	10	strategy	strategy	NOUN
bracis-28373	256	11	.	.	PUNCT
bracis-28373	257	1	finally	finally	ADV
bracis-28373	257	2	,	,	PUNCT
bracis-28373	257	3	however	however	ADV
bracis-28373	257	4	,	,	PUNCT
bracis-28373	257	5	we	we	PRON
bracis-28373	257	6	noticed	notice	VERB
bracis-28373	257	7	that	that	SCONJ
bracis-28373	257	8	for	for	ADP
bracis-28373	257	9	the	the	DET
bracis-28373	257	10	recall	recall	NOUN
bracis-28373	257	11	metric	metric	PROPN
bracis-28373	257	12	,	,	PUNCT
bracis-28373	257	13	our	our	PRON
bracis-28373	257	14	proposal	proposal	NOUN
bracis-28373	257	15	had	have	VERB
bracis-28373	257	16	better	well	ADJ
bracis-28373	257	17	performance	performance	NOUN
bracis-28373	257	18	(	(	PUNCT
bracis-28373	257	19	being	be	AUX
bracis-28373	257	20	more	more	ADV
bracis-28373	257	21	effective	effective	ADJ
bracis-28373	257	22	in	in	ADP
bracis-28373	257	23	degrading	degrade	VERB
bracis-28373	257	24	this	this	DET
bracis-28373	257	25	metric	metric	NOUN
bracis-28373	257	26	in	in	ADP
bracis-28373	257	27	the	the	DET
bracis-28373	257	28	federation	federation	NOUN
bracis-28373	257	29	result	result	PROPN
bracis-28373	257	30	)	)	PUNCT
bracis-28373	257	31	.	.	PUNCT
bracis-28373	258	1	for	for	ADP
bracis-28373	258	2	the	the	DET
bracis-28373	258	3	geometric	geometric	ADJ
bracis-28373	258	4	defense	defense	NOUN
bracis-28373	258	5	strategy	strategy	NOUN
bracis-28373	258	6	,	,	PUNCT
bracis-28373	258	7	we	we	PRON
bracis-28373	258	8	observed	observe	VERB
bracis-28373	258	9	that	that	SCONJ
bracis-28373	258	10	our	our	PRON
bracis-28373	258	11	approach	approach	NOUN
bracis-28373	258	12	achieved	achieve	VERB
bracis-28373	258	13	the	the	DET
bracis-28373	258	14	highest	high	ADJ
bracis-28373	258	15	degradation	degradation	NOUN
bracis-28373	258	16	of	of	ADP
bracis-28373	258	17	the	the	DET
bracis-28373	258	18	model	model	NOUN
bracis-28373	258	19	.	.	PUNCT
bracis-28373	259	1	for	for	ADP
bracis-28373	259	2	the	the	DET
bracis-28373	259	3	accuracy	accuracy	NOUN
bracis-28373	259	4	metric	metric	NOUN
bracis-28373	259	5	,	,	PUNCT
bracis-28373	259	6	our	our	PRON
bracis-28373	259	7	model	model	NOUN
bracis-28373	259	8	obtained	obtain	VERB
bracis-28373	259	9	0.701	0.701	NUM
bracis-28373	259	10	,	,	PUNCT
bracis-28373	259	11	showing	show	VERB
bracis-28373	259	12	a	a	DET
bracis-28373	259	13	difference	difference	NOUN
bracis-28373	259	14	of	of	ADP
bracis-28373	259	15	18.48	18.48	NUM
bracis-28373	259	16	%	%	NOUN
bracis-28373	259	17	when	when	SCONJ
bracis-28373	259	18	compared	compare	VERB
bracis-28373	259	19	to	to	ADP
bracis-28373	259	20	the	the	DET
bracis-28373	259	21	approach	approach	NOUN
bracis-28373	259	22	without	without	ADP
bracis-28373	259	23	malicious	malicious	ADJ
bracis-28373	259	24	clients	client	NOUN
bracis-28373	259	25	.	.	PUNCT
bracis-28373	260	1	the	the	DET
bracis-28373	260	2	second	second	ADV
bracis-28373	260	3	-	-	PUNCT
bracis-28373	260	4	best	good	ADJ
bracis-28373	260	5	attack	attack	NOUN
bracis-28373	260	6	proposal	proposal	NOUN
bracis-28373	260	7	achieved	achieve	VERB
bracis-28373	260	8	a	a	DET
bracis-28373	260	9	degradation	degradation	NOUN
bracis-28373	260	10	of	of	ADP
bracis-28373	260	11	8.02	8.02	NUM
bracis-28373	260	12	%	%	NOUN
bracis-28373	260	13	compared	compare	VERB
bracis-28373	260	14	to	to	ADP
bracis-28373	260	15	the	the	DET
bracis-28373	260	16	model	model	NOUN
bracis-28373	260	17	without	without	ADP
bracis-28373	260	18	any	any	DET
bracis-28373	260	19	attack	attack	NOUN
bracis-28373	260	20	(	(	PUNCT
bracis-28373	260	21	none	none	NOUN
bracis-28373	260	22	)	)	PUNCT
bracis-28373	260	23	.	.	PUNCT
bracis-28373	261	1	we	we	PRON
bracis-28373	261	2	observed	observe	VERB
bracis-28373	261	3	that	that	SCONJ
bracis-28373	261	4	this	this	DET
bracis-28373	261	5	behavior	behavior	NOUN
bracis-28373	261	6	is	be	AUX
bracis-28373	261	7	consistent	consistent	ADJ
bracis-28373	261	8	for	for	ADP
bracis-28373	261	9	the	the	DET
bracis-28373	261	10	other	other	ADJ
bracis-28373	261	11	metrics	metric	NOUN
bracis-28373	261	12	,	,	PUNCT
bracis-28373	261	13	where	where	SCONJ
bracis-28373	261	14	our	our	PRON
bracis-28373	261	15	approach	approach	NOUN
bracis-28373	261	16	achieved	achieve	VERB
bracis-28373	261	17	a	a	DET
bracis-28373	261	18	precision	precision	NOUN
bracis-28373	261	19	of	of	ADP
bracis-28373	261	20	0.707	0.707	NUM
bracis-28373	261	21	,	,	PUNCT
bracis-28373	261	22	recall	recall	NOUN
bracis-28373	261	23	of	of	ADP
bracis-28373	261	24	0.703	0.703	NUM
bracis-28373	261	25	,	,	PUNCT
bracis-28373	261	26	and	and	CCONJ
bracis-28373	261	27	f1	f1	NOUN
bracis-28373	261	28	-	-	PUNCT
bracis-28373	261	29	score	score	NOUN
bracis-28373	261	30	of	of	ADP
bracis-28373	261	31	0.705	0.705	NUM
bracis-28373	261	32	.	.	PUNCT
bracis-28373	262	1	we	we	PRON
bracis-28373	262	2	also	also	ADV
bracis-28373	262	3	observed	observe	VERB
bracis-28373	262	4	similar	similar	ADJ
bracis-28373	262	5	behavior	behavior	NOUN
bracis-28373	262	6	for	for	ADP
bracis-28373	262	7	the	the	DET
bracis-28373	262	8	krum	krum	PROPN
bracis-28373	262	9	,	,	PUNCT
bracis-28373	262	10	norm	norm	NOUN
bracis-28373	262	11	,	,	PUNCT
bracis-28373	262	12	and	and	CCONJ
bracis-28373	262	13	trimmed	trimmed	ADJ
bracis-28373	262	14	experiments	experiment	NOUN
bracis-28373	262	15	,	,	PUNCT
bracis-28373	262	16	indicating	indicate	VERB
bracis-28373	262	17	that	that	SCONJ
bracis-28373	262	18	the	the	DET
bracis-28373	262	19	attack	attack	NOUN
bracis-28373	262	20	strategy	strategy	NOUN
bracis-28373	262	21	significantly	significantly	ADV
bracis-28373	262	22	impacted	impact	VERB
bracis-28373	262	23	the	the	DET
bracis-28373	262	24	defense	defense	NOUN
bracis-28373	262	25	mechanisms	mechanism	NOUN
bracis-28373	262	26	’	'	PUNCT
bracis-28373	262	27	performance	performance	NOUN
bracis-28373	262	28	.	.	PUNCT
bracis-28373	263	1	based	base	VERB
bracis-28373	263	2	on	on	ADP
bracis-28373	263	3	the	the	DET
bracis-28373	263	4	results	result	NOUN
bracis-28373	263	5	,	,	PUNCT
bracis-28373	263	6	our	our	PRON
bracis-28373	263	7	proposed	propose	VERB
bracis-28373	263	8	approach	approach	NOUN
bracis-28373	263	9	was	be	AUX
bracis-28373	263	10	superior	superior	ADJ
bracis-28373	263	11	in	in	ADP
bracis-28373	263	12	four	four	NUM
bracis-28373	263	13	scenarios	scenario	NOUN
bracis-28373	263	14	,	,	PUNCT
bracis-28373	263	15	while	while	SCONJ
bracis-28373	263	16	the	the	DET
bracis-28373	263	17	stat	stat	NOUN
bracis-28373	263	18	-	-	PUNCT
bracis-28373	263	19	opt	opt	NOUN
bracis-28373	263	20	proposal	proposal	NOUN
bracis-28373	263	21	was	be	AUX
bracis-28373	263	22	better	well	ADJ
bracis-28373	263	23	in	in	ADP
bracis-28373	263	24	only	only	ADV
bracis-28373	263	25	two	two	NUM
bracis-28373	263	26	.	.	PUNCT
bracis-28373	264	1	this	this	DET
bracis-28373	264	2	conclusion	conclusion	NOUN
bracis-28373	264	3	happens	happen	VERB
bracis-28373	264	4	because	because	SCONJ
bracis-28373	264	5	the	the	DET
bracis-28373	264	6	stat	stat	NOUN
bracis-28373	264	7	-	-	PUNCT
bracis-28373	264	8	opt	opt	NOUN
bracis-28373	264	9	proposal	proposal	NOUN
bracis-28373	264	10	manipulates	manipulate	VERB
bracis-28373	264	11	the	the	DET
bracis-28373	264	12	gradient	gradient	NOUN
bracis-28373	264	13	to	to	PART
bracis-28373	264	14	attack	attack	VERB
bracis-28373	264	15	the	the	DET
bracis-28373	264	16	model	model	NOUN
bracis-28373	264	17	,	,	PUNCT
bracis-28373	264	18	while	while	SCONJ
bracis-28373	264	19	our	our	PRON
bracis-28373	264	20	approach	approach	NOUN
bracis-28373	264	21	only	only	ADV
bracis-28373	264	22	performs	perform	VERB
bracis-28373	264	23	a	a	DET
bracis-28373	264	24	label	label	NOUN
bracis-28373	264	25	change	change	NOUN
bracis-28373	264	26	attack	attack	NOUN
bracis-28373	264	27	.	.	PUNCT
bracis-28373	265	1	manipulating	manipulate	VERB
bracis-28373	265	2	the	the	DET
bracis-28373	265	3	gradient	gradient	NOUN
bracis-28373	265	4	allows	allow	VERB
bracis-28373	265	5	the	the	DET
bracis-28373	265	6	stat	stat	NOUN
bracis-28373	265	7	-	-	PUNCT
bracis-28373	265	8	opt	opt	NOUN
bracis-28373	265	9	approach	approach	NOUN
bracis-28373	265	10	to	to	PART
bracis-28373	265	11	have	have	VERB
bracis-28373	265	12	finer	fine	ADJ
bracis-28373	265	13	control	control	NOUN
bracis-28373	265	14	over	over	ADP
bracis-28373	265	15	changes	change	NOUN
bracis-28373	265	16	made	make	VERB
bracis-28373	265	17	to	to	PART
bracis-28373	265	18	model	model	VERB
bracis-28373	265	19	weights	weight	NOUN
bracis-28373	265	20	,	,	PUNCT
bracis-28373	265	21	making	make	VERB
bracis-28373	265	22	the	the	DET
bracis-28373	265	23	attack	attack	NOUN
bracis-28373	265	24	more	more	ADV
bracis-28373	265	25	effective	effective	ADJ
bracis-28373	265	26	.	.	PUNCT
bracis-28373	266	1	furthermore	furthermore	ADV
bracis-28373	266	2	,	,	PUNCT
bracis-28373	266	3	the	the	DET
bracis-28373	266	4	stat	stat	NOUN
bracis-28373	266	5	-	-	PUNCT
bracis-28373	266	6	opt	opt	NOUN
bracis-28373	266	7	approach	approach	NOUN
bracis-28373	266	8	can	can	AUX
bracis-28373	266	9	exploit	exploit	VERB
bracis-28373	266	10	the	the	DET
bracis-28373	266	11	model	model	NOUN
bracis-28373	266	12	’s	’s	PART
bracis-28373	266	13	internal	internal	ADJ
bracis-28373	266	14	structure	structure	NOUN
bracis-28373	266	15	,	,	PUNCT
bracis-28373	266	16	which	which	PRON
bracis-28373	266	17	can	can	AUX
bracis-28373	266	18	lead	lead	VERB
bracis-28373	266	19	to	to	ADP
bracis-28373	266	20	more	more	ADV
bracis-28373	266	21	sophisticated	sophisticated	ADJ
bracis-28373	266	22	and	and	CCONJ
bracis-28373	266	23	challenging	challenging	ADJ
bracis-28373	266	24	to	to	PART
bracis-28373	266	25	detect	detect	VERB
bracis-28373	266	26	attacks	attack	NOUN
bracis-28373	266	27	,	,	PUNCT
bracis-28373	266	28	unlike	unlike	ADP
bracis-28373	266	29	our	our	PRON
bracis-28373	266	30	approach	approach	NOUN
bracis-28373	266	31	,	,	PUNCT
bracis-28373	266	32	which	which	PRON
bracis-28373	266	33	only	only	ADV
bracis-28373	266	34	performs	perform	VERB
bracis-28373	266	35	a	a	DET
bracis-28373	266	36	label	label	NOUN
bracis-28373	266	37	change	change	NOUN
bracis-28373	266	38	attack	attack	NOUN
bracis-28373	266	39	.	.	PUNCT
bracis-28373	267	1	however	however	ADV
bracis-28373	267	2	,	,	PUNCT
bracis-28373	267	3	our	our	PRON
bracis-28373	267	4	proposed	propose	VERB
bracis-28373	267	5	approach	approach	NOUN
bracis-28373	267	6	outperformed	outperform	VERB
bracis-28373	267	7	the	the	DET
bracis-28373	267	8	other	other	ADJ
bracis-28373	267	9	defense	defense	NOUN
bracis-28373	267	10	mechanisms	mechanism	NOUN
bracis-28373	267	11	in	in	ADP
bracis-28373	267	12	the	the	DET
bracis-28373	267	13	remaining	remain	VERB
bracis-28373	267	14	scenarios	scenario	NOUN
bracis-28373	267	15	.	.	PUNCT
bracis-28373	268	1	this	this	PRON
bracis-28373	268	2	indicates	indicate	VERB
bracis-28373	268	3	that	that	SCONJ
bracis-28373	268	4	our	our	PRON
bracis-28373	268	5	approach	approach	NOUN
bracis-28373	268	6	is	be	AUX
bracis-28373	268	7	more	more	ADV
bracis-28373	268	8	effective	effective	ADJ
bracis-28373	268	9	for	for	ADP
bracis-28373	268	10	attacking	attack	VERB
bracis-28373	268	11	federated	federated	ADJ
bracis-28373	268	12	learning	learning	NOUN
bracis-28373	268	13	models	model	NOUN
bracis-28373	268	14	than	than	ADP
bracis-28373	268	15	the	the	DET
bracis-28373	268	16	label	label	NOUN
bracis-28373	268	17	attack	attack	NOUN
bracis-28373	268	18	in	in	ADP
bracis-28373	268	19	the	the	DET
bracis-28373	268	20	stat	stat	NOUN
bracis-28373	268	21	-	-	PUNCT
bracis-28373	268	22	opt	opt	NOUN
bracis-28373	268	23	proposal	proposal	NOUN
bracis-28373	268	24	.	.	PUNCT
bracis-28373	269	1	overall	overall	ADV
bracis-28373	269	2	,	,	PUNCT
bracis-28373	269	3	our	our	PRON
bracis-28373	269	4	approach	approach	NOUN
bracis-28373	269	5	is	be	AUX
bracis-28373	269	6	a	a	DET
bracis-28373	269	7	powerful	powerful	ADJ
bracis-28373	269	8	tool	tool	NOUN
bracis-28373	269	9	for	for	ADP
bracis-28373	269	10	evaluating	evaluate	VERB
bracis-28373	269	11	the	the	DET
bracis-28373	269	12	robustness	robustness	NOUN
bracis-28373	269	13	of	of	ADP
bracis-28373	269	14	federated	federated	ADJ
bracis-28373	269	15	learning	learning	NOUN
bracis-28373	269	16	models	model	NOUN
bracis-28373	269	17	and	and	CCONJ
bracis-28373	269	18	improving	improve	VERB
bracis-28373	269	19	their	their	PRON
bracis-28373	269	20	defenses	defense	NOUN
bracis-28373	269	21	against	against	ADP
bracis-28373	269	22	label	label	NOUN
bracis-28373	269	23	change	change	NOUN
bracis-28373	269	24	attacks	attack	NOUN
bracis-28373	269	25	.	.	PUNCT
bracis-28373	270	1	6	6	NUM
bracis-28373	270	2	conclusion	conclusion	NOUN
bracis-28373	270	3	this	this	DET
bracis-28373	270	4	paper	paper	NOUN
bracis-28373	270	5	proposes	propose	VERB
bracis-28373	270	6	a	a	DET
bracis-28373	270	7	new	new	ADJ
bracis-28373	270	8	labeling	labeling	NOUN
bracis-28373	270	9	attack	attack	NOUN
bracis-28373	270	10	model	model	NOUN
bracis-28373	270	11	for	for	ADP
bracis-28373	270	12	federated	federated	ADJ
bracis-28373	270	13	environments	environment	NOUN
bracis-28373	270	14	using	use	VERB
bracis-28373	270	15	bayesian	bayesian	NOUN
bracis-28373	270	16	neural	neural	ADJ
bracis-28373	270	17	networks	network	NOUN
bracis-28373	270	18	.	.	PUNCT
bracis-28373	271	1	the	the	DET
bracis-28373	271	2	approach	approach	NOUN
bracis-28373	271	3	is	be	AUX
bracis-28373	271	4	based	base	VERB
bracis-28373	271	5	on	on	ADP
bracis-28373	271	6	a	a	DET
bracis-28373	271	7	model	model	NOUN
bracis-28373	271	8	trained	train	VERB
bracis-28373	271	9	with	with	ADP
bracis-28373	271	10	the	the	DET
bracis-28373	271	11	marginal	marginal	ADJ
bracis-28373	271	12	likelihood	likelihood	NOUN
bracis-28373	271	13	loss	loss	NOUN
bracis-28373	271	14	function	function	NOUN
bracis-28373	271	15	that	that	PRON
bracis-28373	271	16	maximizes	maximize	VERB
bracis-28373	271	17	the	the	DET
bracis-28373	271	18	adherence	adherence	NOUN
bracis-28373	271	19	of	of	ADP
bracis-28373	271	20	malicious	malicious	ADJ
bracis-28373	271	21	data	datum	NOUN
bracis-28373	271	22	to	to	ADP
bracis-28373	271	23	the	the	DET
bracis-28373	271	24	model	model	NOUN
bracis-28373	271	25	while	while	SCONJ
bracis-28373	271	26	also	also	ADV
bracis-28373	271	27	estimating	estimate	VERB
bracis-28373	271	28	a	a	DET
bracis-28373	271	29	poisoned	poison	VERB
bracis-28373	271	30	model	model	NOUN
bracis-28373	271	31	with	with	ADP
bracis-28373	271	32	lower	low	ADJ
bracis-28373	271	33	complexity	complexity	NOUN
bracis-28373	271	34	,	,	PUNCT
bracis-28373	271	35	making	make	VERB
bracis-28373	271	36	it	it	PRON
bracis-28373	271	37	difficult	difficult	ADJ
bracis-28373	271	38	to	to	PART
bracis-28373	271	39	detect	detect	VERB
bracis-28373	271	40	attacks	attack	NOUN
bracis-28373	271	41	in	in	ADP
bracis-28373	271	42	federated	federated	ADJ
bracis-28373	271	43	environments	environment	NOUN
bracis-28373	271	44	.	.	PUNCT
bracis-28373	272	1	in	in	ADP
bracis-28373	272	2	federated	federated	ADJ
bracis-28373	272	3	environments	environment	NOUN
bracis-28373	272	4	,	,	PUNCT
bracis-28373	272	5	it	it	PRON
bracis-28373	272	6	is	be	AUX
bracis-28373	272	7	essential	essential	ADJ
bracis-28373	272	8	to	to	PART
bracis-28373	272	9	ensure	ensure	VERB
bracis-28373	272	10	the	the	DET
bracis-28373	272	11	security	security	NOUN
bracis-28373	272	12	and	and	CCONJ
bracis-28373	272	13	privacy	privacy	NOUN
bracis-28373	272	14	of	of	ADP
bracis-28373	272	15	user	user	NOUN
bracis-28373	272	16	data	datum	NOUN
bracis-28373	272	17	and	and	CCONJ
bracis-28373	272	18	the	the	DET
bracis-28373	272	19	reliability	reliability	NOUN
bracis-28373	272	20	of	of	ADP
bracis-28373	272	21	built	build	VERB
bracis-28373	272	22	models	model	NOUN
bracis-28373	272	23	.	.	PUNCT
bracis-28373	273	1	however	however	ADV
bracis-28373	273	2	,	,	PUNCT
bracis-28373	273	3	machine	machine	NOUN
bracis-28373	273	4	learning	learn	VERB
bracis-28373	273	5	techniques	technique	NOUN
bracis-28373	273	6	in	in	ADP
bracis-28373	273	7	federated	federated	ADJ
bracis-28373	273	8	environments	environment	NOUN
bracis-28373	273	9	still	still	ADV
bracis-28373	273	10	present	present	VERB
bracis-28373	273	11	vulnerabilities	vulnerability	NOUN
bracis-28373	273	12	since	since	SCONJ
bracis-28373	273	13	the	the	DET
bracis-28373	273	14	model	model	NOUN
bracis-28373	273	15	is	be	AUX
bracis-28373	273	16	trained	train	VERB
bracis-28373	273	17	based	base	VERB
bracis-28373	273	18	on	on	ADP
bracis-28373	273	19	data	datum	NOUN
bracis-28373	273	20	from	from	ADP
bracis-28373	273	21	multiple	multiple	ADJ
bracis-28373	273	22	users	user	NOUN
bracis-28373	273	23	,	,	PUNCT
bracis-28373	273	24	including	include	VERB
bracis-28373	273	25	possible	possible	ADJ
bracis-28373	273	26	attackers	attacker	NOUN
bracis-28373	273	27	.	.	PUNCT
bracis-28373	274	1	the	the	DET
bracis-28373	274	2	evaluation	evaluation	NOUN
bracis-28373	274	3	of	of	ADP
bracis-28373	274	4	different	different	ADJ
bracis-28373	274	5	defense	defense	NOUN
bracis-28373	274	6	mechanisms	mechanism	NOUN
bracis-28373	274	7	against	against	ADP
bracis-28373	274	8	various	various	ADJ
bracis-28373	274	9	attacks	attack	NOUN
bracis-28373	274	10	in	in	ADP
bracis-28373	274	11	federated	federated	ADJ
bracis-28373	274	12	learning	learning	NOUN
bracis-28373	274	13	showed	show	VERB
bracis-28373	274	14	that	that	SCONJ
bracis-28373	274	15	the	the	DET
bracis-28373	274	16	performance	performance	NOUN
bracis-28373	274	17	of	of	ADP
bracis-28373	274	18	defense	defense	NOUN
bracis-28373	274	19	mechanisms	mechanism	NOUN
bracis-28373	274	20	varies	vary	VERB
bracis-28373	274	21	according	accord	VERB
bracis-28373	274	22	to	to	ADP
bracis-28373	274	23	the	the	DET
bracis-28373	274	24	attack	attack	NOUN
bracis-28373	274	25	proposal	proposal	NOUN
bracis-28373	274	26	and	and	CCONJ
bracis-28373	274	27	the	the	DET
bracis-28373	274	28	type	type	NOUN
bracis-28373	274	29	of	of	ADP
bracis-28373	274	30	defense	defense	NOUN
bracis-28373	274	31	used	use	VERB
bracis-28373	274	32	.	.	PUNCT
bracis-28373	275	1	however	however	ADV
bracis-28373	275	2	,	,	PUNCT
bracis-28373	275	3	in	in	ADP
bracis-28373	275	4	general	general	ADJ
bracis-28373	275	5	,	,	PUNCT
bracis-28373	275	6	our	our	PRON
bracis-28373	275	7	proposed	propose	VERB
bracis-28373	275	8	attack	attack	NOUN
bracis-28373	275	9	was	be	AUX
bracis-28373	275	10	more	more	ADV
bracis-28373	275	11	effective	effective	ADJ
bracis-28373	275	12	in	in	ADP
bracis-28373	275	13	all	all	DET
bracis-28373	275	14	scenarios	scenario	NOUN
bracis-28373	275	15	.	.	PUNCT
bracis-28373	276	1	the	the	DET
bracis-28373	276	2	results	result	NOUN
bracis-28373	276	3	also	also	ADV
bracis-28373	276	4	showed	show	VERB
bracis-28373	276	5	that	that	SCONJ
bracis-28373	276	6	the	the	DET
bracis-28373	276	7	proposed	propose	VERB
bracis-28373	276	8	attack	attack	NOUN
bracis-28373	276	9	method	method	NOUN
bracis-28373	276	10	was	be	AUX
bracis-28373	276	11	highly	highly	ADV
bracis-28373	276	12	influential	influential	ADJ
bracis-28373	276	13	in	in	ADP
bracis-28373	276	14	degrading	degrade	VERB
bracis-28373	276	15	the	the	DET
bracis-28373	276	16	model	model	NOUN
bracis-28373	276	17	’s	’s	PART
bracis-28373	276	18	performance	performance	NOUN
bracis-28373	276	19	.	.	PUNCT
bracis-28373	277	1	therefore	therefore	ADV
bracis-28373	277	2	,	,	PUNCT
bracis-28373	277	3	it	it	PRON
bracis-28373	277	4	is	be	AUX
bracis-28373	277	5	crucial	crucial	ADJ
bracis-28373	277	6	to	to	PART
bracis-28373	277	7	consider	consider	VERB
bracis-28373	277	8	the	the	DET
bracis-28373	277	9	proposed	propose	VERB
bracis-28373	277	10	attack	attack	NOUN
bracis-28373	277	11	model	model	NOUN
bracis-28373	277	12	when	when	SCONJ
bracis-28373	277	13	designing	design	VERB
bracis-28373	277	14	defense	defense	NOUN
bracis-28373	277	15	mechanisms	mechanism	NOUN
bracis-28373	277	16	for	for	ADP
bracis-28373	277	17	federated	federated	ADJ
bracis-28373	277	18	learning	learning	NOUN
bracis-28373	277	19	systems	system	NOUN
bracis-28373	277	20	.	.	PUNCT
bracis-28373	278	1	furthermore	furthermore	ADV
bracis-28373	278	2	,	,	PUNCT
bracis-28373	278	3	the	the	DET
bracis-28373	278	4	findings	finding	NOUN
bracis-28373	278	5	suggest	suggest	VERB
bracis-28373	278	6	that	that	SCONJ
bracis-28373	278	7	future	future	ADJ
bracis-28373	278	8	research	research	NOUN
bracis-28373	278	9	should	should	AUX
bracis-28373	278	10	focus	focus	VERB
bracis-28373	278	11	on	on	ADP
bracis-28373	278	12	developing	develop	VERB
bracis-28373	278	13	more	more	ADV
bracis-28373	278	14	effective	effective	ADJ
bracis-28373	278	15	defense	defense	NOUN
bracis-28373	278	16	mechanisms	mechanism	NOUN
bracis-28373	278	17	to	to	PART
bracis-28373	278	18	mitigate	mitigate	VERB
bracis-28373	278	19	the	the	DET
bracis-28373	278	20	risks	risk	NOUN
bracis-28373	278	21	associated	associate	VERB
bracis-28373	278	22	with	with	ADP
bracis-28373	278	23	the	the	DET
bracis-28373	278	24	proposed	propose	VERB
bracis-28373	278	25	attack	attack	NOUN
bracis-28373	278	26	.	.	PUNCT
bracis-28373	279	1	references	reference	NOUN
bracis-28373	279	2	alistarh	alistarh	PROPN
bracis-28373	279	3	,	,	PUNCT
bracis-28373	279	4	d.	d.	PROPN
bracis-28373	279	5	,	,	PUNCT
bracis-28373	279	6	allen	allen	PROPN
bracis-28373	279	7	-	-	PUNCT
bracis-28373	279	8	zhu	zhu	PROPN
bracis-28373	279	9	,	,	PUNCT
bracis-28373	279	10	z.	z.	PROPN
bracis-28373	279	11	,	,	PUNCT
bracis-28373	279	12	li	li	PROPN
bracis-28373	279	13	,	,	PUNCT
bracis-28373	279	14	j.	j.	PROPN
bracis-28373	279	15	:	:	PUNCT
bracis-28373	279	16	byzantine	byzantine	ADJ
bracis-28373	279	17	stochastic	stochastic	ADJ
bracis-28373	279	18	gradient	gradient	ADJ
bracis-28373	279	19	descent	descent	NOUN
bracis-28373	279	20	.	.	PUNCT
bracis-28373	280	1	in	in	ADP
bracis-28373	280	2	:	:	PUNCT
bracis-28373	280	3	advances	advance	NOUN
bracis-28373	280	4	in	in	ADP
bracis-28373	280	5	neural	neural	ADJ
bracis-28373	280	6	information	information	NOUN
bracis-28373	280	7	processing	processing	NOUN
bracis-28373	280	8	systems	system	NOUN
bracis-28373	280	9	,	,	PUNCT
bracis-28373	280	10	vol	vol	NOUN
bracis-28373	280	11	.	.	PUNCT
bracis-28373	280	12	31	31	NUM
bracis-28373	280	13	.	.	PUNCT
bracis-28373	281	1	curran	curran	PROPN
bracis-28373	281	2	associates	associates	PROPN
bracis-28373	281	3	,	,	PUNCT
bracis-28373	281	4	inc	inc	PROPN
bracis-28373	281	5	.	.	PROPN
bracis-28373	281	6	(	(	PUNCT
bracis-28373	281	7	2018	2018	NUM
bracis-28373	281	8	)	)	PUNCT
bracis-28373	281	9	google	google	NOUN
bracis-28373	281	10	scholar	scholar	NOUN
bracis-28373	281	11	  	  	SPACE
bracis-28373	281	12	bansal	bansal	NOUN
bracis-28373	281	13	,	,	PUNCT
bracis-28373	281	14	y.	y.	PROPN
bracis-28373	281	15	,	,	PUNCT
bracis-28373	281	16	et	et	PROPN
bracis-28373	281	17	al	al	PROPN
bracis-28373	281	18	.	.	PROPN
bracis-28373	281	19	:	:	PUNCT
bracis-28373	282	1	for	for	ADP
bracis-28373	282	2	self	self	NOUN
bracis-28373	282	3	-	-	PUNCT
bracis-28373	282	4	supervised	supervise	VERB
bracis-28373	282	5	learning	learning	NOUN
bracis-28373	282	6	,	,	PUNCT
bracis-28373	282	7	rationality	rationality	NOUN
bracis-28373	282	8	implies	imply	VERB
bracis-28373	282	9	generalization	generalization	NOUN
bracis-28373	282	10	,	,	PUNCT
bracis-28373	282	11	provably	provably	ADV
bracis-28373	282	12	.	.	PUNCT
bracis-28373	283	1	in	in	ADP
bracis-28373	283	2	:	:	PUNCT
bracis-28373	283	3	international	international	ADJ
bracis-28373	283	4	conference	conference	NOUN
bracis-28373	283	5	on	on	ADP
bracis-28373	283	6	learning	learn	VERB
bracis-28373	283	7	representations	representation	NOUN
bracis-28373	283	8	(	(	PUNCT
bracis-28373	283	9	iclr	iclr	NOUN
bracis-28373	283	10	)	)	PUNCT
bracis-28373	283	11	(	(	PUNCT
bracis-28373	283	12	2020	2020	NUM
bracis-28373	283	13	)	)	PUNCT
bracis-28373	283	14	google	google	PROPN
bracis-28373	283	15	scholar	scholar	NOUN
bracis-28373	283	16	  	  	SPACE
bracis-28373	283	17	bhagoji	bhagoji	NOUN
bracis-28373	283	18	,	,	PUNCT
bracis-28373	283	19	a.n	a.n	PROPN
bracis-28373	283	20	.	.	PROPN
bracis-28373	283	21	,	,	PUNCT
bracis-28373	283	22	chakraborty	chakraborty	PROPN
bracis-28373	283	23	,	,	PUNCT
bracis-28373	283	24	s.	s.	PROPN
bracis-28373	283	25	,	,	PUNCT
bracis-28373	283	26	mittal	mittal	PROPN
bracis-28373	283	27	,	,	PUNCT
bracis-28373	283	28	p.	p.	PROPN
bracis-28373	283	29	,	,	PUNCT
bracis-28373	283	30	calo	calo	PROPN
bracis-28373	283	31	,	,	PUNCT
bracis-28373	283	32	s.	s.	PROPN
bracis-28373	283	33	:	:	PUNCT
bracis-28373	283	34	analyzing	analyze	VERB
bracis-28373	283	35	federated	federated	ADJ
bracis-28373	283	36	learning	learn	VERB
bracis-28373	283	37	through	through	ADP
bracis-28373	283	38	an	an	DET
bracis-28373	283	39	adversarial	adversarial	ADJ
bracis-28373	283	40	lens	len	NOUN
bracis-28373	283	41	.	.	PUNCT
bracis-28373	284	1	in	in	ADP
bracis-28373	284	2	:	:	PUNCT
bracis-28373	284	3	international	international	ADJ
bracis-28373	284	4	conference	conference	NOUN
bracis-28373	284	5	on	on	ADP
bracis-28373	284	6	machine	machine	NOUN
bracis-28373	284	7	learning	learning	NOUN
bracis-28373	284	8	(	(	PUNCT
bracis-28373	284	9	icml	icml	PROPN
bracis-28373	284	10	)	)	PUNCT
bracis-28373	284	11	,	,	PUNCT
bracis-28373	284	12	vol	vol	NOUN
bracis-28373	284	13	.	.	PROPN
bracis-28373	284	14	97	97	NUM
bracis-28373	284	15	(	(	PUNCT
bracis-28373	284	16	2019	2019	NUM
bracis-28373	284	17	)	)	PUNCT
bracis-28373	284	18	google	google	NOUN
bracis-28373	284	19	scholar	scholar	NOUN
bracis-28373	284	20	  	  	SPACE
bracis-28373	284	21	blanchard	blanchard	NOUN
bracis-28373	284	22	,	,	PUNCT
bracis-28373	284	23	p.	p.	PROPN
bracis-28373	284	24	,	,	PUNCT
bracis-28373	284	25	el	el	PROPN
bracis-28373	284	26	mhamdi	mhamdi	PROPN
bracis-28373	284	27	,	,	PUNCT
bracis-28373	284	28	e.m	e.m	PROPN
bracis-28373	284	29	.	.	PROPN
bracis-28373	284	30	,	,	PUNCT
bracis-28373	284	31	guerraoui	guerraoui	PROPN
bracis-28373	284	32	,	,	PUNCT
bracis-28373	284	33	r.	r.	PROPN
bracis-28373	284	34	,	,	PUNCT
bracis-28373	284	35	stainer	stainer	NOUN
bracis-28373	284	36	,	,	PUNCT
bracis-28373	284	37	j.	j.	PROPN
bracis-28373	284	38	:	:	PUNCT
bracis-28373	284	39	machine	machine	NOUN
bracis-28373	284	40	learning	learn	VERB
bracis-28373	284	41	with	with	ADP
bracis-28373	284	42	adversaries	adversary	NOUN
bracis-28373	284	43	:	:	PUNCT
bracis-28373	284	44	byzantine	byzantine	ADJ
bracis-28373	284	45	tolerant	tolerant	ADJ
bracis-28373	284	46	gradient	gradient	ADJ
bracis-28373	284	47	descent	descent	NOUN
bracis-28373	284	48	.	.	PUNCT
bracis-28373	285	1	in	in	ADP
bracis-28373	285	2	:	:	PUNCT
bracis-28373	285	3	advances	advance	NOUN
bracis-28373	285	4	in	in	ADP
bracis-28373	285	5	neural	neural	ADJ
bracis-28373	285	6	information	information	NOUN
bracis-28373	285	7	processing	processing	NOUN
bracis-28373	285	8	systems	system	NOUN
bracis-28373	285	9	(	(	PUNCT
bracis-28373	285	10	neurips	neurip	NOUN
bracis-28373	285	11	)	)	PUNCT
bracis-28373	285	12	,	,	PUNCT
bracis-28373	285	13	vol	vol	NOUN
bracis-28373	285	14	.	.	PROPN
bracis-28373	285	15	30	30	NUM
bracis-28373	285	16	(	(	PUNCT
bracis-28373	285	17	2017	2017	NUM
bracis-28373	285	18	)	)	PUNCT
bracis-28373	285	19	google	google	PROPN
bracis-28373	285	20	scholar	scholar	NOUN
bracis-28373	285	21	  	  	SPACE
bracis-28373	285	22	chen	chen	PROPN
bracis-28373	285	23	,	,	PUNCT
bracis-28373	285	24	l.y	l.y	PROPN
bracis-28373	285	25	.	.	PROPN
bracis-28373	285	26	,	,	PUNCT
bracis-28373	285	27	chiu	chiu	PROPN
bracis-28373	285	28	,	,	PUNCT
bracis-28373	285	29	t.c	t.c	PROPN
bracis-28373	285	30	.	.	PROPN
bracis-28373	285	31	,	,	PUNCT
bracis-28373	285	32	pang	pang	NOUN
bracis-28373	285	33	,	,	PUNCT
bracis-28373	285	34	a.c	a.c	PROPN
bracis-28373	285	35	.	.	PROPN
bracis-28373	285	36	,	,	PUNCT
bracis-28373	285	37	cheng	cheng	PROPN
bracis-28373	285	38	,	,	PUNCT
bracis-28373	285	39	l.c	l.c	PROPN
bracis-28373	285	40	.	.	PROPN
bracis-28373	285	41	:	:	PUNCT
bracis-28373	286	1	fedequal	fedequal	ADJ
bracis-28373	286	2	:	:	PUNCT
bracis-28373	286	3	defending	defend	VERB
bracis-28373	286	4	model	model	NOUN
bracis-28373	286	5	poisoning	poisoning	NOUN
bracis-28373	286	6	attacks	attack	NOUN
bracis-28373	286	7	in	in	ADP
bracis-28373	286	8	heterogeneous	heterogeneous	ADJ
bracis-28373	286	9	federated	federated	ADJ
bracis-28373	286	10	learning	learning	NOUN
bracis-28373	286	11	.	.	PUNCT
bracis-28373	287	1	in	in	ADP
bracis-28373	287	2	:	:	PUNCT
bracis-28373	287	3	2021	2021	NUM
bracis-28373	287	4	ieee	ieee	PROPN
bracis-28373	287	5	global	global	PROPN
bracis-28373	287	6	communications	communications	PROPN
bracis-28373	287	7	conference	conference	NOUN
bracis-28373	287	8	(	(	PUNCT
bracis-28373	287	9	globecom	globecom	PROPN
bracis-28373	287	10	)	)	PUNCT
bracis-28373	287	11	,	,	PUNCT
bracis-28373	287	12	pp	pp	ADV
bracis-28373	287	13	.	.	PUNCT
bracis-28373	288	1	1–6	1–6	NUM
bracis-28373	288	2	(	(	PUNCT
bracis-28373	288	3	2021	2021	NUM
bracis-28373	288	4	)	)	PUNCT
bracis-28373	288	5	google	google	NOUN
bracis-28373	288	6	scholar	scholar	NOUN
bracis-28373	288	7	  	  	SPACE
bracis-28373	288	8	dao	dao	PROPN
bracis-28373	288	9	,	,	PUNCT
bracis-28373	288	10	n.n	n.n	PROPN
bracis-28373	288	11	.	.	PROPN
bracis-28373	288	12	,	,	PUNCT
bracis-28373	288	13	et	et	PROPN
bracis-28373	288	14	al	al	PROPN
bracis-28373	288	15	.	.	PUNCT
bracis-28373	288	16	:	:	PUNCT
bracis-28373	289	1	securing	secure	VERB
bracis-28373	289	2	heterogeneous	heterogeneous	ADJ
bracis-28373	289	3	iot	iot	NOUN
bracis-28373	289	4	with	with	ADP
bracis-28373	289	5	intelligent	intelligent	ADJ
bracis-28373	289	6	ddos	ddo	NOUN
bracis-28373	289	7	attack	attack	NOUN
bracis-28373	289	8	behavior	behavior	NOUN
bracis-28373	289	9	learning	learn	VERB
bracis-28373	289	10	.	.	PUNCT
bracis-28373	290	1	ieee	ieee	PROPN
bracis-28373	290	2	syst	syst	PROPN
bracis-28373	290	3	.	.	PUNCT
bracis-28373	291	1	j.	j.	PROPN
bracis-28373	291	2	16(2	16(2	PROPN
bracis-28373	291	3	)	)	PUNCT
bracis-28373	291	4	,	,	PUNCT
bracis-28373	291	5	1974–1983	1974–1983	NUM
bracis-28373	291	6	(	(	PUNCT
bracis-28373	291	7	2022	2022	NUM
bracis-28373	291	8	)	)	PUNCT
bracis-28373	291	9	article	article	NOUN
bracis-28373	291	10	  	  	SPACE
bracis-28373	291	11	google	google	PROPN
bracis-28373	291	12	scholar	scholar	NOUN
bracis-28373	291	13	  	  	SPACE
bracis-28373	291	14	fang	fang	NOUN
bracis-28373	291	15	,	,	PUNCT
bracis-28373	291	16	m.	m.	NOUN
bracis-28373	291	17	,	,	PUNCT
bracis-28373	291	18	cao	cao	PROPN
bracis-28373	291	19	,	,	PUNCT
bracis-28373	291	20	x.	x.	PROPN
bracis-28373	291	21	,	,	PUNCT
bracis-28373	291	22	jia	jia	PROPN
bracis-28373	291	23	,	,	PUNCT
bracis-28373	291	24	j.	j.	PROPN
bracis-28373	291	25	,	,	PUNCT
bracis-28373	291	26	gong	gong	PROPN
bracis-28373	291	27	,	,	PUNCT
bracis-28373	291	28	n.z	n.z	PROPN
bracis-28373	291	29	.	.	PROPN
bracis-28373	291	30	:	:	PUNCT
bracis-28373	292	1	local	local	ADJ
bracis-28373	292	2	model	model	NOUN
bracis-28373	292	3	poisoning	poisoning	NOUN
bracis-28373	292	4	attacks	attack	NOUN
bracis-28373	292	5	to	to	ADP
bracis-28373	292	6	byzantine	byzantine	ADJ
bracis-28373	292	7	-	-	PUNCT
bracis-28373	292	8	robust	robust	ADJ
bracis-28373	292	9	federated	federated	ADJ
bracis-28373	292	10	learning	learning	NOUN
bracis-28373	292	11	.	.	PUNCT
bracis-28373	293	1	in	in	ADP
bracis-28373	293	2	:	:	PUNCT
bracis-28373	293	3	proceedings	proceeding	NOUN
bracis-28373	293	4	of	of	ADP
bracis-28373	293	5	the	the	DET
bracis-28373	293	6	29th	29th	ADJ
bracis-28373	293	7	usenix	usenix	NOUN
bracis-28373	293	8	conference	conference	NOUN
bracis-28373	293	9	on	on	ADP
bracis-28373	293	10	security	security	NOUN
bracis-28373	293	11	symposium	symposium	NOUN
bracis-28373	293	12	(	(	PUNCT
bracis-28373	293	13	sec	sec	PROPN
bracis-28373	293	14	)	)	PUNCT
bracis-28373	293	15	(	(	PUNCT
bracis-28373	293	16	2020	2020	NUM
bracis-28373	293	17	)	)	PUNCT
bracis-28373	293	18	google	google	PROPN
bracis-28373	293	19	scholar	scholar	NOUN
bracis-28373	293	20	  	  	SPACE
bracis-28373	293	21	gal	gal	PROPN
bracis-28373	293	22	,	,	PUNCT
bracis-28373	293	23	y.	y.	PROPN
bracis-28373	293	24	,	,	PUNCT
bracis-28373	293	25	ghahramani	ghahramani	PROPN
bracis-28373	293	26	,	,	PUNCT
bracis-28373	293	27	z.	z.	PROPN
bracis-28373	293	28	:	:	PUNCT
bracis-28373	293	29	dropout	dropout	NOUN
bracis-28373	293	30	as	as	ADP
bracis-28373	293	31	a	a	DET
bracis-28373	293	32	bayesian	bayesian	NOUN
bracis-28373	293	33	approximation	approximation	NOUN
bracis-28373	293	34	:	:	PUNCT
bracis-28373	293	35	representing	represent	VERB
bracis-28373	293	36	model	model	NOUN
bracis-28373	293	37	uncertainty	uncertainty	NOUN
bracis-28373	293	38	in	in	ADP
bracis-28373	293	39	deep	deep	ADJ
bracis-28373	293	40	learning	learning	NOUN
bracis-28373	293	41	.	.	PUNCT
bracis-28373	294	1	in	in	ADP
bracis-28373	294	2	:	:	PUNCT
bracis-28373	294	3	proceedings	proceeding	NOUN
bracis-28373	294	4	of	of	ADP
bracis-28373	294	5	the	the	DET
bracis-28373	294	6	33rd	33rd	ADJ
bracis-28373	294	7	international	international	ADJ
bracis-28373	294	8	conference	conference	NOUN
bracis-28373	294	9	on	on	ADP
bracis-28373	294	10	machine	machine	NOUN
bracis-28373	294	11	learning	learning	NOUN
bracis-28373	294	12	(	(	PUNCT
bracis-28373	294	13	icml	icml	PROPN
bracis-28373	294	14	)	)	PUNCT
bracis-28373	294	15	(	(	PUNCT
bracis-28373	294	16	2016	2016	NUM
bracis-28373	294	17	)	)	PUNCT
bracis-28373	294	18	google	google	PROPN
bracis-28373	294	19	scholar	scholar	NOUN
bracis-28373	294	20	  	  	SPACE
bracis-28373	294	21	ghahramani	ghahramani	NOUN
bracis-28373	294	22	,	,	PUNCT
bracis-28373	294	23	z.	z.	PROPN
bracis-28373	294	24	:	:	PUNCT
bracis-28373	294	25	probabilistic	probabilistic	ADJ
bracis-28373	294	26	machine	machine	NOUN
bracis-28373	294	27	learning	learning	NOUN
bracis-28373	294	28	and	and	CCONJ
bracis-28373	294	29	artificial	artificial	ADJ
bracis-28373	294	30	intelligence	intelligence	NOUN
bracis-28373	294	31	.	.	PUNCT
bracis-28373	295	1	nature	nature	NOUN
bracis-28373	295	2	521(7553	521(7553	NUM
bracis-28373	295	3	)	)	PUNCT
bracis-28373	295	4	,	,	PUNCT
bracis-28373	295	5	452–459	452–459	NUM
bracis-28373	295	6	(	(	PUNCT
bracis-28373	295	7	2015	2015	NUM
bracis-28373	295	8	)	)	PUNCT
bracis-28373	295	9	article	article	NOUN
bracis-28373	295	10	  	  	SPACE
bracis-28373	295	11	google	google	PROPN
bracis-28373	295	12	scholar	scholar	NOUN
bracis-28373	295	13	  	  	SPACE
bracis-28373	295	14	guo	guo	PROPN
bracis-28373	295	15	,	,	PUNCT
bracis-28373	295	16	c.	c.	PROPN
bracis-28373	295	17	,	,	PUNCT
bracis-28373	295	18	pleiss	pleiss	NOUN
bracis-28373	295	19	,	,	PUNCT
bracis-28373	295	20	g.	g.	PROPN
bracis-28373	295	21	,	,	PUNCT
bracis-28373	295	22	sun	sun	NOUN
bracis-28373	295	23	,	,	PUNCT
bracis-28373	295	24	y.	y.	PROPN
bracis-28373	295	25	,	,	PUNCT
bracis-28373	295	26	weinberger	weinberger	PROPN
bracis-28373	295	27	,	,	PUNCT
bracis-28373	295	28	k.q	k.q	PROPN
bracis-28373	295	29	.	.	PROPN
bracis-28373	295	30	:	:	PUNCT
bracis-28373	296	1	on	on	ADP
bracis-28373	296	2	calibration	calibration	NOUN
bracis-28373	296	3	of	of	ADP
bracis-28373	296	4	modern	modern	ADJ
bracis-28373	296	5	neural	neural	ADJ
bracis-28373	296	6	networks	network	NOUN
bracis-28373	296	7	.	.	PUNCT
bracis-28373	297	1	in	in	ADP
bracis-28373	297	2	:	:	PUNCT
bracis-28373	297	3	proceedings	proceeding	NOUN
bracis-28373	297	4	of	of	ADP
bracis-28373	297	5	the	the	DET
bracis-28373	297	6	34th	34th	ADJ
bracis-28373	297	7	international	international	ADJ
bracis-28373	297	8	conference	conference	NOUN
bracis-28373	297	9	on	on	ADP
bracis-28373	297	10	machine	machine	NOUN
bracis-28373	297	11	learning	learning	NOUN
bracis-28373	297	12	,	,	PUNCT
bracis-28373	297	13	icml	icml	VERB
bracis-28373	297	14	2017	2017	NUM
bracis-28373	297	15	(	(	PUNCT
bracis-28373	297	16	2017	2017	NUM
bracis-28373	297	17	)	)	PUNCT
bracis-28373	297	18	google	google	PROPN
bracis-28373	297	19	scholar	scholar	NOUN
bracis-28373	297	20	  	  	SPACE
bracis-28373	297	21	immer	immer	NOUN
bracis-28373	297	22	,	,	PUNCT
bracis-28373	297	23	a.	a.	PROPN
bracis-28373	297	24	,	,	PUNCT
bracis-28373	297	25	et	et	PROPN
bracis-28373	297	26	al	al	PROPN
bracis-28373	297	27	.	.	PUNCT
bracis-28373	297	28	:	:	PUNCT
bracis-28373	298	1	scalable	scalable	ADJ
bracis-28373	298	2	marginal	marginal	ADJ
bracis-28373	298	3	likelihood	likelihood	NOUN
bracis-28373	298	4	estimation	estimation	NOUN
bracis-28373	298	5	for	for	ADP
bracis-28373	298	6	model	model	NOUN
bracis-28373	298	7	selection	selection	NOUN
bracis-28373	298	8	in	in	ADP
bracis-28373	298	9	deep	deep	ADJ
bracis-28373	298	10	learning	learning	NOUN
bracis-28373	298	11	.	.	PUNCT
bracis-28373	299	1	in	in	ADP
bracis-28373	299	2	:	:	PUNCT
bracis-28373	299	3	international	international	ADJ
bracis-28373	299	4	conference	conference	NOUN
bracis-28373	299	5	on	on	ADP
bracis-28373	299	6	machine	machine	NOUN
bracis-28373	299	7	learning	learning	NOUN
bracis-28373	299	8	(	(	PUNCT
bracis-28373	299	9	icml	icml	PROPN
bracis-28373	299	10	)	)	PUNCT
bracis-28373	299	11	,	,	PUNCT
bracis-28373	299	12	vol	vol	NOUN
bracis-28373	299	13	.	.	PROPN
bracis-28373	299	14	139	139	NUM
bracis-28373	299	15	,	,	PUNCT
bracis-28373	299	16	pp	pp	ADJ
bracis-28373	299	17	.	.	PUNCT
bracis-28373	299	18	4563–4573	4563–4573	NUM
bracis-28373	299	19	(	(	PUNCT
bracis-28373	299	20	2021	2021	NUM
bracis-28373	299	21	)	)	PUNCT
bracis-28373	299	22	google	google	NOUN
bracis-28373	299	23	scholar	scholar	NOUN
bracis-28373	299	24	  	  	SPACE
bracis-28373	299	25	jagielski	jagielski	NOUN
bracis-28373	299	26	,	,	PUNCT
bracis-28373	299	27	m.	m.	NOUN
bracis-28373	299	28	,	,	PUNCT
bracis-28373	299	29	oprea	oprea	PROPN
bracis-28373	299	30	,	,	PUNCT
bracis-28373	299	31	a.	a.	NOUN
bracis-28373	299	32	,	,	PUNCT
bracis-28373	299	33	biggio	biggio	PROPN
bracis-28373	299	34	,	,	PUNCT
bracis-28373	299	35	b.	b.	PROPN
bracis-28373	299	36	,	,	PUNCT
bracis-28373	299	37	liu	liu	PROPN
bracis-28373	299	38	,	,	PUNCT
bracis-28373	299	39	c.	c.	PROPN
bracis-28373	299	40	,	,	PUNCT
bracis-28373	299	41	nita	nita	PROPN
bracis-28373	299	42	-	-	PUNCT
bracis-28373	299	43	rotaru	rotaru	PROPN
bracis-28373	299	44	,	,	PUNCT
bracis-28373	299	45	c.	c.	PROPN
bracis-28373	299	46	,	,	PUNCT
bracis-28373	299	47	li	li	PROPN
bracis-28373	299	48	,	,	PUNCT
bracis-28373	299	49	b.	b.	PROPN
bracis-28373	299	50	:	:	PUNCT
bracis-28373	299	51	manipulating	manipulate	VERB
bracis-28373	299	52	machine	machine	NOUN
bracis-28373	299	53	learning	learning	NOUN
bracis-28373	299	54	:	:	PUNCT
bracis-28373	299	55	poisoning	poisoning	NOUN
bracis-28373	299	56	attacks	attack	NOUN
bracis-28373	299	57	and	and	CCONJ
bracis-28373	299	58	countermeasures	countermeasure	NOUN
bracis-28373	299	59	for	for	ADP
bracis-28373	299	60	regression	regression	NOUN
bracis-28373	299	61	learning	learn	VERB
bracis-28373	299	62	.	.	PUNCT
bracis-28373	300	1	in	in	ADP
bracis-28373	300	2	:	:	PUNCT
bracis-28373	300	3	2018	2018	NUM
bracis-28373	300	4	ieee	ieee	NOUN
bracis-28373	300	5	symposium	symposium	NOUN
bracis-28373	300	6	on	on	ADP
bracis-28373	300	7	security	security	NOUN
bracis-28373	300	8	and	and	CCONJ
bracis-28373	300	9	privacy	privacy	NOUN
bracis-28373	300	10	(	(	PUNCT
bracis-28373	300	11	sp	sp	NOUN
bracis-28373	300	12	)	)	PUNCT
bracis-28373	300	13	,	,	PUNCT
bracis-28373	300	14	pp	pp	PROPN
bracis-28373	300	15	.	.	PUNCT
bracis-28373	301	1	19–35	19–35	NUM
bracis-28373	301	2	(	(	PUNCT
bracis-28373	301	3	2018	2018	NUM
bracis-28373	301	4	)	)	PUNCT
bracis-28373	301	5	google	google	PROPN
bracis-28373	301	6	scholar	scholar	NOUN
bracis-28373	301	7	  	  	SPACE
bracis-28373	301	8	lamport	lamport	NOUN
bracis-28373	301	9	,	,	PUNCT
bracis-28373	301	10	l.	l.	PROPN
bracis-28373	301	11	,	,	PUNCT
bracis-28373	301	12	shostak	shostak	PROPN
bracis-28373	301	13	,	,	PUNCT
bracis-28373	301	14	r.	r.	PROPN
bracis-28373	301	15	,	,	PUNCT
bracis-28373	301	16	pease	pease	PROPN
bracis-28373	301	17	,	,	PUNCT
bracis-28373	301	18	m.	m.	NOUN
bracis-28373	301	19	:	:	PUNCT
bracis-28373	301	20	the	the	DET
bracis-28373	301	21	byzantine	byzantine	ADJ
bracis-28373	301	22	generals	general	NOUN
bracis-28373	301	23	problem	problem	NOUN
bracis-28373	301	24	.	.	PUNCT
bracis-28373	302	1	acm	acm	PROPN
bracis-28373	302	2	trans	trans	PROPN
bracis-28373	302	3	.	.	PUNCT
bracis-28373	303	1	programm	programm	PROPN
bracis-28373	303	2	.	.	PUNCT
bracis-28373	304	1	lang	lang	PROPN
bracis-28373	304	2	.	.	PUNCT
bracis-28373	305	1	syst	syst	PROPN
bracis-28373	305	2	.	.	PUNCT
bracis-28373	306	1	4(3	4(3	NUM
bracis-28373	306	2	)	)	PUNCT
bracis-28373	306	3	,	,	PUNCT
bracis-28373	306	4	382–401	382–401	NUM
bracis-28373	306	5	(	(	PUNCT
bracis-28373	306	6	1982	1982	NUM
bracis-28373	306	7	)	)	PUNCT
bracis-28373	306	8	article	article	NOUN
bracis-28373	306	9	  	  	SPACE
bracis-28373	306	10	math	math	NOUN
bracis-28373	306	11	  	  	SPACE
bracis-28373	306	12	google	google	PROPN
bracis-28373	306	13	scholar	scholar	NOUN
bracis-28373	306	14	  	  	SPACE
bracis-28373	306	15	li	li	PROPN
bracis-28373	306	16	,	,	PUNCT
bracis-28373	306	17	t.	t.	PROPN
bracis-28373	306	18	,	,	PUNCT
bracis-28373	306	19	sahu	sahu	PROPN
bracis-28373	306	20	,	,	PUNCT
bracis-28373	306	21	a.k	a.k	PROPN
bracis-28373	306	22	.	.	PROPN
bracis-28373	306	23	,	,	PUNCT
bracis-28373	306	24	talwalkar	talwalkar	PROPN
bracis-28373	306	25	,	,	PUNCT
bracis-28373	306	26	a.	a.	PROPN
bracis-28373	306	27	,	,	PUNCT
bracis-28373	306	28	smith	smith	PROPN
bracis-28373	306	29	,	,	PUNCT
bracis-28373	306	30	v.	v.	PROPN
bracis-28373	306	31	:	:	PUNCT
bracis-28373	306	32	federated	federated	ADJ
bracis-28373	306	33	learning	learning	NOUN
bracis-28373	306	34	:	:	PUNCT
bracis-28373	306	35	challenges	challenge	NOUN
bracis-28373	306	36	,	,	PUNCT
bracis-28373	306	37	methods	method	NOUN
bracis-28373	306	38	,	,	PUNCT
bracis-28373	306	39	and	and	CCONJ
bracis-28373	306	40	future	future	ADJ
bracis-28373	306	41	directions	direction	NOUN
bracis-28373	306	42	.	.	PUNCT
bracis-28373	307	1	ieee	ieee	NOUN
bracis-28373	307	2	signal	signal	NOUN
bracis-28373	307	3	process	process	NOUN
bracis-28373	307	4	.	.	PUNCT
bracis-28373	308	1	mag	mag	INTJ
bracis-28373	308	2	.	.	PROPN
bracis-28373	309	1	37	37	NUM
bracis-28373	309	2	,	,	PUNCT
bracis-28373	309	3	50–60	50–60	NUM
bracis-28373	309	4	(	(	PUNCT
bracis-28373	309	5	2020	2020	NUM
bracis-28373	309	6	)	)	PUNCT
bracis-28373	309	7	google	google	PROPN
bracis-28373	309	8	scholar	scholar	NOUN
bracis-28373	309	9	  	  	SPACE
bracis-28373	309	10	mcmahan	mcmahan	PROPN
bracis-28373	309	11	,	,	PUNCT
bracis-28373	309	12	b.	b.	PROPN
bracis-28373	309	13	,	,	PUNCT
bracis-28373	309	14	moore	moore	PROPN
bracis-28373	309	15	,	,	PUNCT
bracis-28373	309	16	e.	e.	PROPN
bracis-28373	309	17	,	,	PUNCT
bracis-28373	309	18	ramage	ramage	NOUN
bracis-28373	309	19	,	,	PUNCT
bracis-28373	309	20	d.	d.	PROPN
bracis-28373	309	21	,	,	PUNCT
bracis-28373	309	22	hampson	hampson	PROPN
bracis-28373	309	23	,	,	PUNCT
bracis-28373	309	24	s.	s.	PROPN
bracis-28373	309	25	,	,	PUNCT
bracis-28373	309	26	arcas	arcas	PROPN
bracis-28373	309	27	,	,	PUNCT
bracis-28373	309	28	b.a	b.a	PROPN
bracis-28373	309	29	.	.	PUNCT
bracis-28373	309	30	:	:	PUNCT
bracis-28373	310	1	communication	communication	NOUN
bracis-28373	310	2	-	-	PUNCT
bracis-28373	310	3	efficient	efficient	ADJ
bracis-28373	310	4	learning	learning	NOUN
bracis-28373	310	5	of	of	ADP
bracis-28373	310	6	deep	deep	ADJ
bracis-28373	310	7	networks	network	NOUN
bracis-28373	310	8	from	from	ADP
bracis-28373	310	9	decentralized	decentralized	ADJ
bracis-28373	310	10	data	datum	NOUN
bracis-28373	310	11	.	.	PUNCT
bracis-28373	311	1	in	in	ADP
bracis-28373	311	2	:	:	PUNCT
bracis-28373	311	3	proceedings	proceeding	NOUN
bracis-28373	311	4	of	of	ADP
bracis-28373	311	5	the	the	DET
bracis-28373	311	6	international	international	ADJ
bracis-28373	311	7	conference	conference	NOUN
bracis-28373	311	8	on	on	ADP
bracis-28373	311	9	artificial	artificial	ADJ
bracis-28373	311	10	intelligence	intelligence	NOUN
bracis-28373	311	11	and	and	CCONJ
bracis-28373	311	12	statistics	statistic	NOUN
bracis-28373	311	13	(	(	PUNCT
bracis-28373	311	14	aistats	aistat	NOUN
bracis-28373	311	15	)	)	PUNCT
bracis-28373	311	16	,	,	PUNCT
bracis-28373	311	17	pp	pp	ADP
bracis-28373	311	18	.	.	PUNCT
bracis-28373	312	1	1273–1282	1273–1282	NUM
bracis-28373	312	2	(	(	PUNCT
bracis-28373	312	3	2017	2017	NUM
bracis-28373	312	4	)	)	PUNCT
bracis-28373	312	5	google	google	NOUN
bracis-28373	312	6	scholar	scholar	NOUN
bracis-28373	312	7	  	  	SPACE
bracis-28373	312	8	pillutla	pillutla	NOUN
bracis-28373	312	9	,	,	PUNCT
bracis-28373	312	10	k.	k.	PROPN
bracis-28373	312	11	,	,	PUNCT
bracis-28373	312	12	kakade	kakade	PROPN
bracis-28373	312	13	,	,	PUNCT
bracis-28373	312	14	s.m	s.m	PROPN
bracis-28373	312	15	.	.	PROPN
bracis-28373	312	16	,	,	PUNCT
bracis-28373	312	17	harchaoui	harchaoui	PROPN
bracis-28373	312	18	,	,	PUNCT
bracis-28373	312	19	z.	z.	PROPN
bracis-28373	312	20	:	:	PUNCT
bracis-28373	312	21	robust	robust	ADJ
bracis-28373	312	22	aggregation	aggregation	NOUN
bracis-28373	312	23	for	for	ADP
bracis-28373	312	24	federated	federated	ADJ
bracis-28373	312	25	learning	learning	NOUN
bracis-28373	312	26	.	.	PUNCT
bracis-28373	313	1	ieee	ieee	PROPN
bracis-28373	313	2	trans	trans	PROPN
bracis-28373	313	3	.	.	PROPN
bracis-28373	313	4	signal	signal	PROPN
bracis-28373	313	5	process	process	NOUN
bracis-28373	313	6	.	.	PUNCT
bracis-28373	314	1	70	70	NUM
bracis-28373	314	2	,	,	PUNCT
bracis-28373	314	3	1142–1154	1142–1154	NUM
bracis-28373	314	4	(	(	PUNCT
bracis-28373	314	5	2022	2022	NUM
bracis-28373	314	6	)	)	PUNCT
bracis-28373	314	7	article	article	NOUN
bracis-28373	314	8	  	  	SPACE
bracis-28373	314	9	mathscinet	mathscinet	NOUN
bracis-28373	314	10	  	  	SPACE
bracis-28373	314	11	google	google	PROPN
bracis-28373	314	12	scholar	scholar	NOUN
bracis-28373	314	13	  	  	SPACE
bracis-28373	314	14	rodríguez	rodríguez	NOUN
bracis-28373	314	15	-	-	PUNCT
bracis-28373	314	16	barroso	barroso	PROPN
bracis-28373	314	17	,	,	PUNCT
bracis-28373	314	18	n.	n.	NOUN
bracis-28373	314	19	,	,	PUNCT
bracis-28373	314	20	martínez	martínez	NOUN
bracis-28373	314	21	-	-	PUNCT
bracis-28373	314	22	cámara	cámara	PROPN
bracis-28373	314	23	,	,	PUNCT
bracis-28373	314	24	e.	e.	PROPN
bracis-28373	314	25	,	,	PUNCT
bracis-28373	314	26	luzón	luzón	PROPN
bracis-28373	314	27	,	,	PUNCT
bracis-28373	314	28	m.v	m.v	PROPN
bracis-28373	314	29	.	.	PROPN
bracis-28373	314	30	,	,	PUNCT
bracis-28373	314	31	herrera	herrera	PROPN
bracis-28373	314	32	,	,	PUNCT
bracis-28373	314	33	f.	f.	NOUN
bracis-28373	315	1	:	:	PUNCT
bracis-28373	316	1	dynamic	dynamic	ADJ
bracis-28373	316	2	defense	defense	NOUN
bracis-28373	316	3	against	against	ADP
bracis-28373	316	4	byzantine	byzantine	ADJ
bracis-28373	316	5	poisoning	poisoning	NOUN
bracis-28373	316	6	attacks	attack	NOUN
bracis-28373	316	7	in	in	ADP
bracis-28373	316	8	federated	federated	ADJ
bracis-28373	316	9	learning	learning	NOUN
bracis-28373	316	10	.	.	PUNCT
bracis-28373	317	1	future	future	ADJ
bracis-28373	317	2	gener	gener	PROPN
bracis-28373	317	3	.	.	PUNCT
bracis-28373	318	1	comput	comput	PROPN
bracis-28373	318	2	.	.	PUNCT
bracis-28373	319	1	syst	syst	PROPN
bracis-28373	319	2	.	.	PUNCT
bracis-28373	320	1	133	133	NUM
bracis-28373	320	2	,	,	PUNCT
bracis-28373	320	3	1–9	1–9	NUM
bracis-28373	320	4	(	(	PUNCT
bracis-28373	320	5	2022	2022	NUM
bracis-28373	320	6	)	)	PUNCT
bracis-28373	320	7	article	article	NOUN
bracis-28373	320	8	  	  	SPACE
bracis-28373	320	9	google	google	PROPN
bracis-28373	320	10	scholar	scholar	NOUN
bracis-28373	320	11	  	  	SPACE
bracis-28373	320	12	shejwalkar	shejwalkar	PROPN
bracis-28373	320	13	,	,	PUNCT
bracis-28373	320	14	v.	v.	PROPN
bracis-28373	320	15	,	,	PUNCT
bracis-28373	320	16	houmansadr	houmansadr	PROPN
bracis-28373	320	17	,	,	PUNCT
bracis-28373	320	18	a.	a.	NOUN
bracis-28373	320	19	,	,	PUNCT
bracis-28373	320	20	kairouz	kairouz	PROPN
bracis-28373	320	21	,	,	PUNCT
bracis-28373	320	22	p.	p.	NOUN
bracis-28373	320	23	,	,	PUNCT
bracis-28373	320	24	ramage	ramage	NOUN
bracis-28373	320	25	,	,	PUNCT
bracis-28373	320	26	d.	d.	PROPN
bracis-28373	320	27	:	:	PUNCT
bracis-28373	320	28	back	back	ADV
bracis-28373	320	29	to	to	ADP
bracis-28373	320	30	the	the	DET
bracis-28373	320	31	drawing	drawing	NOUN
bracis-28373	320	32	board	board	NOUN
bracis-28373	320	33	:	:	PUNCT
bracis-28373	320	34	a	a	DET
bracis-28373	320	35	critical	critical	ADJ
bracis-28373	320	36	evaluation	evaluation	NOUN
bracis-28373	320	37	of	of	ADP
bracis-28373	320	38	poisoning	poisoning	NOUN
bracis-28373	320	39	attacks	attack	NOUN
bracis-28373	320	40	on	on	ADP
bracis-28373	320	41	production	production	NOUN
bracis-28373	320	42	federated	federated	ADJ
bracis-28373	320	43	learning	learning	NOUN
bracis-28373	320	44	.	.	PUNCT
bracis-28373	321	1	in	in	ADP
bracis-28373	321	2	:	:	PUNCT
bracis-28373	321	3	2022	2022	NUM
bracis-28373	321	4	ieee	ieee	NOUN
bracis-28373	321	5	symposium	symposium	NOUN
bracis-28373	321	6	on	on	ADP
bracis-28373	321	7	security	security	NOUN
bracis-28373	321	8	and	and	CCONJ
bracis-28373	321	9	privacy	privacy	NOUN
bracis-28373	321	10	(	(	PUNCT
bracis-28373	321	11	sp	sp	NOUN
bracis-28373	321	12	)	)	PUNCT
bracis-28373	321	13	,	,	PUNCT
bracis-28373	321	14	pp	pp	ADP
bracis-28373	321	15	.	.	PUNCT
bracis-28373	322	1	1354–1371	1354–1371	NUM
bracis-28373	322	2	(	(	PUNCT
bracis-28373	322	3	2022	2022	NUM
bracis-28373	322	4	)	)	PUNCT
bracis-28373	322	5	google	google	PROPN
bracis-28373	322	6	scholar	scholar	NOUN
bracis-28373	322	7	  	  	SPACE
bracis-28373	322	8	sun	sun	NOUN
bracis-28373	322	9	,	,	PUNCT
bracis-28373	322	10	g.	g.	PROPN
bracis-28373	322	11	,	,	PUNCT
bracis-28373	322	12	cong	cong	NOUN
bracis-28373	322	13	,	,	PUNCT
bracis-28373	322	14	y.	y.	PROPN
bracis-28373	322	15	,	,	PUNCT
bracis-28373	322	16	dong	dong	PROPN
bracis-28373	322	17	,	,	PUNCT
bracis-28373	322	18	j.	j.	PROPN
bracis-28373	322	19	,	,	PUNCT
bracis-28373	322	20	wang	wang	PROPN
bracis-28373	322	21	,	,	PUNCT
bracis-28373	322	22	q.	q.	PROPN
bracis-28373	322	23	,	,	PUNCT
bracis-28373	322	24	lyu	lyu	PROPN
bracis-28373	322	25	,	,	PUNCT
bracis-28373	322	26	l.	l.	PROPN
bracis-28373	322	27	,	,	PUNCT
bracis-28373	322	28	liu	liu	PROPN
bracis-28373	322	29	,	,	PUNCT
bracis-28373	322	30	j.	j.	PROPN
bracis-28373	322	31	:	:	PUNCT
bracis-28373	322	32	data	datum	NOUN
bracis-28373	322	33	poisoning	poisoning	NOUN
bracis-28373	322	34	attacks	attack	NOUN
bracis-28373	322	35	on	on	ADP
bracis-28373	322	36	federated	federated	ADJ
bracis-28373	322	37	machine	machine	NOUN
bracis-28373	322	38	learning	learning	NOUN
bracis-28373	322	39	.	.	PUNCT
bracis-28373	323	1	ieee	ieee	NOUN
bracis-28373	323	2	internet	internet	NOUN
bracis-28373	323	3	things	thing	NOUN
bracis-28373	323	4	j.	j.	PROPN
bracis-28373	323	5	9(13	9(13	NUM
bracis-28373	323	6	)	)	PUNCT
bracis-28373	323	7	,	,	PUNCT
bracis-28373	323	8	11365–11375	11365–11375	NUM
bracis-28373	323	9	(	(	PUNCT
bracis-28373	323	10	2022	2022	NUM
bracis-28373	323	11	)	)	PUNCT
bracis-28373	323	12	article	article	NOUN
bracis-28373	323	13	  	  	SPACE
bracis-28373	323	14	google	google	PROPN
bracis-28373	323	15	scholar	scholar	NOUN
bracis-28373	323	16	  	  	SPACE
bracis-28373	323	17	sun	sun	NOUN
bracis-28373	323	18	,	,	PUNCT
bracis-28373	323	19	z.	z.	PROPN
bracis-28373	323	20	,	,	PUNCT
bracis-28373	323	21	kairouz	kairouz	PROPN
bracis-28373	323	22	,	,	PUNCT
bracis-28373	323	23	p.	p.	PROPN
bracis-28373	323	24	,	,	PUNCT
bracis-28373	323	25	suresh	suresh	PROPN
bracis-28373	323	26	,	,	PUNCT
bracis-28373	323	27	a.t	a.t	PROPN
bracis-28373	323	28	.	.	PROPN
bracis-28373	323	29	,	,	PUNCT
bracis-28373	323	30	mcmahan	mcmahan	PROPN
bracis-28373	323	31	,	,	PUNCT
bracis-28373	323	32	h.b	h.b	PROPN
bracis-28373	323	33	.	.	PROPN
bracis-28373	323	34	:	:	PUNCT
bracis-28373	323	35	can	can	AUX
bracis-28373	323	36	you	you	PRON
bracis-28373	323	37	really	really	ADV
bracis-28373	323	38	backdoor	backdoor	VERB
bracis-28373	323	39	federated	federated	ADJ
bracis-28373	323	40	learning	learning	NOUN
bracis-28373	323	41	?	?	PUNCT
bracis-28373	324	1	(	(	PUNCT
bracis-28373	324	2	2019	2019	NUM
bracis-28373	324	3	)	)	PUNCT
bracis-28373	324	4	google	google	PROPN
bracis-28373	324	5	scholar	scholar	NOUN
bracis-28373	324	6	  	  	SPACE
bracis-28373	324	7	wang	wang	PROPN
bracis-28373	324	8	,	,	PUNCT
bracis-28373	324	9	h.	h.	PROPN
bracis-28373	324	10	,	,	PUNCT
bracis-28373	324	11	et	et	PROPN
bracis-28373	324	12	al	al	PROPN
bracis-28373	324	13	.	.	PUNCT
bracis-28373	324	14	:	:	PUNCT
bracis-28373	325	1	attack	attack	NOUN
bracis-28373	325	2	of	of	ADP
bracis-28373	325	3	the	the	DET
bracis-28373	325	4	tails	tail	NOUN
bracis-28373	325	5	:	:	PUNCT
bracis-28373	325	6	yes	yes	INTJ
bracis-28373	325	7	,	,	PUNCT
bracis-28373	325	8	you	you	PRON
bracis-28373	325	9	really	really	ADV
bracis-28373	325	10	can	can	AUX
bracis-28373	325	11	backdoor	backdoor	VERB
bracis-28373	325	12	federated	federated	ADJ
bracis-28373	325	13	learning	learning	NOUN
bracis-28373	325	14	.	.	PUNCT
bracis-28373	326	1	in	in	ADP
bracis-28373	326	2	:	:	PUNCT
bracis-28373	326	3	proceedings	proceeding	NOUN
bracis-28373	326	4	of	of	ADP
bracis-28373	326	5	the	the	DET
bracis-28373	326	6	34th	34th	ADJ
bracis-28373	326	7	international	international	ADJ
bracis-28373	326	8	conference	conference	NOUN
bracis-28373	326	9	on	on	ADP
bracis-28373	326	10	neural	neural	ADJ
bracis-28373	326	11	information	information	NOUN
bracis-28373	326	12	processing	processing	NOUN
bracis-28373	326	13	systems	system	NOUN
bracis-28373	326	14	(	(	PUNCT
bracis-28373	326	15	neurips	neurip	NOUN
bracis-28373	326	16	)	)	PUNCT
bracis-28373	326	17	.	.	PUNCT
bracis-28373	327	1	red	red	ADJ
bracis-28373	327	2	hook	hook	NOUN
bracis-28373	327	3	,	,	PUNCT
bracis-28373	327	4	ny	ny	PROPN
bracis-28373	327	5	,	,	PUNCT
bracis-28373	327	6	usa	usa	PROPN
bracis-28373	327	7	(	(	PUNCT
bracis-28373	327	8	2020	2020	NUM
bracis-28373	327	9	)	)	PUNCT
bracis-28373	327	10	google	google	PROPN
bracis-28373	327	11	scholar	scholar	NOUN
bracis-28373	327	12	  	  	SPACE
bracis-28373	327	13	wu	wu	PROPN
bracis-28373	327	14	,	,	PUNCT
bracis-28373	327	15	c.	c.	PROPN
bracis-28373	327	16	,	,	PUNCT
bracis-28373	327	17	wu	wu	PROPN
bracis-28373	327	18	,	,	PUNCT
bracis-28373	327	19	f.	f.	PROPN
bracis-28373	327	20	,	,	PUNCT
bracis-28373	327	21	qi	qi	PROPN
bracis-28373	327	22	,	,	PUNCT
bracis-28373	327	23	t.	t.	PROPN
bracis-28373	327	24	,	,	PUNCT
bracis-28373	327	25	huang	huang	PROPN
bracis-28373	327	26	,	,	PUNCT
bracis-28373	327	27	y.	y.	PROPN
bracis-28373	327	28	,	,	PUNCT
bracis-28373	327	29	xie	xie	PROPN
bracis-28373	327	30	,	,	PUNCT
bracis-28373	327	31	x.	x.	NOUN
bracis-28373	327	32	:	:	PUNCT
bracis-28373	327	33	fedattack	fedattack	NOUN
bracis-28373	327	34	:	:	PUNCT
bracis-28373	327	35	effective	effective	ADJ
bracis-28373	327	36	and	and	CCONJ
bracis-28373	327	37	covert	covert	ADJ
bracis-28373	327	38	poisoning	poisoning	NOUN
bracis-28373	327	39	attack	attack	NOUN
bracis-28373	327	40	on	on	ADP
bracis-28373	327	41	federated	federated	ADJ
bracis-28373	327	42	recommendation	recommendation	NOUN
bracis-28373	327	43	via	via	ADP
bracis-28373	327	44	hard	hard	ADJ
bracis-28373	327	45	sampling	sampling	NOUN
bracis-28373	327	46	.	.	PUNCT
bracis-28373	328	1	in	in	ADP
bracis-28373	328	2	:	:	PUNCT
bracis-28373	328	3	proceedings	proceeding	NOUN
bracis-28373	328	4	of	of	ADP
bracis-28373	328	5	the	the	DET
bracis-28373	328	6	28th	28th	ADJ
bracis-28373	328	7	acm	acm	NOUN
bracis-28373	328	8	sigkdd	sigkdd	NOUN
bracis-28373	328	9	conference	conference	NOUN
bracis-28373	328	10	on	on	ADP
bracis-28373	328	11	knowledge	knowledge	NOUN
bracis-28373	328	12	discovery	discovery	PROPN
bracis-28373	328	13	and	and	CCONJ
bracis-28373	328	14	data	datum	NOUN
bracis-28373	328	15	mining	mining	NOUN
bracis-28373	328	16	(	(	PUNCT
bracis-28373	328	17	kdd	kdd	PROPN
bracis-28373	328	18	)	)	PUNCT
bracis-28373	328	19	,	,	PUNCT
bracis-28373	328	20	pp	pp	PROPN
bracis-28373	328	21	.	.	PUNCT
bracis-28373	329	1	4164–4172	4164–4172	NUM
bracis-28373	329	2	,	,	PUNCT
bracis-28373	329	3	new	new	PROPN
bracis-28373	329	4	york	york	PROPN
bracis-28373	329	5	,	,	PUNCT
bracis-28373	329	6	ny	ny	PROPN
bracis-28373	329	7	,	,	PUNCT
bracis-28373	329	8	usa	usa	PROPN
bracis-28373	329	9	(	(	PUNCT
bracis-28373	329	10	2022	2022	NUM
bracis-28373	329	11	)	)	PUNCT
bracis-28373	329	12	google	google	PROPN
bracis-28373	329	13	scholar	scholar	NOUN
bracis-28373	329	14	  	  	SPACE
bracis-28373	329	15	yin	yin	PROPN
bracis-28373	329	16	,	,	PUNCT
bracis-28373	329	17	d.	d.	PROPN
bracis-28373	329	18	,	,	PUNCT
bracis-28373	329	19	chen	chen	PROPN
bracis-28373	329	20	,	,	PUNCT
bracis-28373	329	21	y.	y.	PROPN
bracis-28373	329	22	,	,	PUNCT
bracis-28373	329	23	kannan	kannan	PROPN
bracis-28373	329	24	,	,	PUNCT
bracis-28373	329	25	r.	r.	PROPN
bracis-28373	329	26	,	,	PUNCT
bracis-28373	329	27	bartlett	bartlett	PROPN
bracis-28373	329	28	,	,	PUNCT
bracis-28373	329	29	p.	p.	NOUN
bracis-28373	329	30	:	:	PUNCT
bracis-28373	329	31	byzantine	byzantine	ADJ
bracis-28373	329	32	-	-	PUNCT
bracis-28373	329	33	robust	robust	ADJ
bracis-28373	329	34	distributed	distributed	ADJ
bracis-28373	329	35	learning	learning	NOUN
bracis-28373	329	36	:	:	PUNCT
bracis-28373	329	37	towards	towards	ADP
bracis-28373	329	38	optimal	optimal	ADJ
bracis-28373	329	39	statistical	statistical	ADJ
bracis-28373	329	40	rates	rate	NOUN
bracis-28373	329	41	.	.	PUNCT
bracis-28373	330	1	in	in	ADP
bracis-28373	330	2	:	:	PUNCT
bracis-28373	330	3	proceedings	proceeding	NOUN
bracis-28373	330	4	of	of	ADP
bracis-28373	330	5	the	the	DET
bracis-28373	330	6	international	international	ADJ
bracis-28373	330	7	conference	conference	NOUN
bracis-28373	330	8	on	on	ADP
bracis-28373	330	9	machine	machine	NOUN
bracis-28373	330	10	learning	learning	NOUN
bracis-28373	330	11	,	,	PUNCT
bracis-28373	330	12	vol	vol	NOUN
bracis-28373	330	13	.	.	PROPN
bracis-28373	330	14	80	80	NUM
bracis-28373	330	15	,	,	PUNCT
bracis-28373	330	16	pp	pp	ADJ
bracis-28373	330	17	.	.	PUNCT
bracis-28373	330	18	5650–5659	5650–5659	NUM
bracis-28373	330	19	(	(	PUNCT
bracis-28373	330	20	2018	2018	NUM
bracis-28373	330	21	)	)	PUNCT
bracis-28373	330	22	google	google	PROPN
bracis-28373	330	23	scholar	scholar	NOUN
bracis-28373	330	24	  	  	SPACE
bracis-28373	330	25	zhang	zhang	PROPN
bracis-28373	330	26	,	,	PUNCT
bracis-28373	330	27	c.	c.	PROPN
bracis-28373	330	28	,	,	PUNCT
bracis-28373	330	29	et	et	PROPN
bracis-28373	330	30	al	al	PROPN
bracis-28373	330	31	.	.	PUNCT
bracis-28373	330	32	:	:	PUNCT
bracis-28373	331	1	understanding	understand	VERB
bracis-28373	331	2	deep	deep	ADJ
bracis-28373	331	3	learning	learning	NOUN
bracis-28373	331	4	(	(	PUNCT
bracis-28373	331	5	still	still	ADV
bracis-28373	331	6	)	)	PUNCT
bracis-28373	331	7	requires	require	VERB
bracis-28373	331	8	rethinking	rethink	VERB
bracis-28373	331	9	generalization	generalization	NOUN
bracis-28373	331	10	.	.	PUNCT
bracis-28373	332	1	commun	commun	PROPN
bracis-28373	332	2	.	.	PUNCT
bracis-28373	333	1	acm	acm	PROPN
bracis-28373	333	2	64(3	64(3	NUM
bracis-28373	333	3	)	)	PUNCT
bracis-28373	333	4	,	,	PUNCT
bracis-28373	333	5	107–115	107–115	NUM
bracis-28373	333	6	(	(	PUNCT
bracis-28373	333	7	2021	2021	NUM
bracis-28373	333	8	)	)	PUNCT
bracis-28373	333	9	article	article	NOUN
bracis-28373	333	10	  	  	SPACE
bracis-28373	333	11	google	google	PROPN
bracis-28373	333	12	scholar	scholar	PROPN
bracis-28373	333	13	  	  	SPACE
bracis-28373	333	14	zhang	zhang	PROPN
bracis-28373	333	15	,	,	PUNCT
bracis-28373	333	16	j.	j.	PROPN
bracis-28373	333	17	,	,	PUNCT
bracis-28373	333	18	chen	chen	PROPN
bracis-28373	333	19	,	,	PUNCT
bracis-28373	333	20	b.	b.	PROPN
bracis-28373	333	21	,	,	PUNCT
bracis-28373	333	22	cheng	cheng	PROPN
bracis-28373	333	23	,	,	PUNCT
bracis-28373	333	24	x.	x.	PROPN
bracis-28373	333	25	,	,	PUNCT
bracis-28373	333	26	binh	binh	ADJ
bracis-28373	333	27	,	,	PUNCT
bracis-28373	333	28	h.t.t	h.t.t	NOUN
bracis-28373	333	29	.	.	PROPN
bracis-28373	333	30	,	,	PUNCT
bracis-28373	333	31	yu	yu	PROPN
bracis-28373	333	32	,	,	PUNCT
bracis-28373	333	33	s.	s.	PROPN
bracis-28373	333	34	:	:	PUNCT
bracis-28373	333	35	poisongan	poisongan	NOUN
bracis-28373	333	36	:	:	PUNCT
bracis-28373	333	37	generative	generative	ADJ
bracis-28373	333	38	poisoning	poisoning	NOUN
bracis-28373	333	39	attacks	attack	NOUN
bracis-28373	333	40	against	against	ADP
bracis-28373	333	41	federated	federated	ADJ
bracis-28373	333	42	learning	learning	NOUN
bracis-28373	333	43	in	in	ADP
bracis-28373	333	44	edge	edge	NOUN
bracis-28373	333	45	computing	computing	NOUN
bracis-28373	333	46	systems	system	NOUN
bracis-28373	333	47	.	.	PUNCT
bracis-28373	334	1	ieee	ieee	NOUN
bracis-28373	334	2	internet	internet	NOUN
bracis-28373	334	3	things	thing	NOUN
bracis-28373	334	4	j.	j.	PROPN
bracis-28373	334	5	8(5	8(5	PROPN
bracis-28373	334	6	)	)	PUNCT
bracis-28373	334	7	,	,	PUNCT
bracis-28373	334	8	3310–3322	3310–3322	NUM
bracis-28373	334	9	(	(	PUNCT
bracis-28373	334	10	2021	2021	NUM
bracis-28373	334	11	)	)	PUNCT
bracis-28373	334	12	article	article	NOUN
bracis-28373	334	13	  	  	SPACE
bracis-28373	334	14	google	google	PROPN
bracis-28373	334	15	scholar	scholar	PROPN
bracis-28373	334	16	  	  	SPACE
bracis-28373	334	17	zhang	zhang	PROPN
bracis-28373	334	18	,	,	PUNCT
bracis-28373	334	19	j.	j.	PROPN
bracis-28373	334	20	,	,	PUNCT
bracis-28373	334	21	chen	chen	PROPN
bracis-28373	334	22	,	,	PUNCT
bracis-28373	334	23	j.	j.	PROPN
bracis-28373	334	24	,	,	PUNCT
bracis-28373	334	25	wu	wu	PROPN
bracis-28373	334	26	,	,	PUNCT
bracis-28373	334	27	d.	d.	PROPN
bracis-28373	334	28	,	,	PUNCT
bracis-28373	334	29	chen	chen	PROPN
bracis-28373	334	30	,	,	PUNCT
bracis-28373	334	31	b.	b.	PROPN
bracis-28373	334	32	,	,	PUNCT
bracis-28373	334	33	yu	yu	PROPN
bracis-28373	334	34	,	,	PUNCT
bracis-28373	334	35	s.	s.	PROPN
bracis-28373	334	36	:	:	PUNCT
bracis-28373	334	37	poisoning	poisoning	NOUN
bracis-28373	334	38	attack	attack	NOUN
bracis-28373	334	39	in	in	ADP
bracis-28373	334	40	federated	federated	ADJ
bracis-28373	334	41	learning	learning	NOUN
bracis-28373	334	42	using	use	VERB
bracis-28373	334	43	generative	generative	ADJ
bracis-28373	334	44	adversarial	adversarial	ADJ
bracis-28373	334	45	nets	net	NOUN
bracis-28373	334	46	.	.	PUNCT
bracis-28373	335	1	in	in	ADP
bracis-28373	335	2	:	:	PUNCT
bracis-28373	335	3	2019	2019	NUM
bracis-28373	335	4	18th	18th	ADJ
bracis-28373	335	5	ieee	ieee	NOUN
bracis-28373	335	6	international	international	ADJ
bracis-28373	335	7	conference	conference	NOUN
bracis-28373	335	8	on	on	ADP
bracis-28373	335	9	trust	trust	NOUN
bracis-28373	335	10	,	,	PUNCT
bracis-28373	335	11	security	security	NOUN
bracis-28373	335	12	and	and	CCONJ
bracis-28373	335	13	privacy	privacy	NOUN
bracis-28373	335	14	in	in	ADP
bracis-28373	335	15	computing	computing	NOUN
bracis-28373	335	16	and	and	CCONJ
bracis-28373	335	17	communications	communication	NOUN
bracis-28373	335	18	(	(	PUNCT
bracis-28373	335	19	trustcom	trustcom	NOUN
bracis-28373	335	20	/	/	SYM
bracis-28373	335	21	bigdatase	bigdatase	NOUN
bracis-28373	335	22	)	)	PUNCT
bracis-28373	335	23	,	,	PUNCT
bracis-28373	335	24	pp	pp	ADP
bracis-28373	335	25	.	.	PUNCT
bracis-28373	336	1	374–380	374–380	NUM
bracis-28373	336	2	(	(	PUNCT
bracis-28373	336	3	2019	2019	NUM
bracis-28373	336	4	)	)	PUNCT
bracis-28373	336	5	google	google	PROPN
bracis-28373	336	6	scholar	scholar	NOUN
bracis-28373	336	7	  	  	SPACE
bracis-28373	336	8	zhao	zhao	NOUN
bracis-28373	336	9	,	,	PUNCT
bracis-28373	336	10	m.	m.	NOUN
bracis-28373	336	11	,	,	PUNCT
bracis-28373	336	12	an	an	PRON
bracis-28373	336	13	,	,	PUNCT
bracis-28373	336	14	b.	b.	PROPN
bracis-28373	336	15	,	,	PUNCT
bracis-28373	336	16	gao	gao	PROPN
bracis-28373	336	17	,	,	PUNCT
bracis-28373	336	18	w.	w.	PROPN
bracis-28373	336	19	,	,	PUNCT
bracis-28373	336	20	zhang	zhang	PROPN
bracis-28373	336	21	,	,	PUNCT
bracis-28373	336	22	t.	t.	PROPN
bracis-28373	336	23	:	:	PUNCT
bracis-28373	336	24	efficient	efficient	ADJ
bracis-28373	336	25	label	label	NOUN
bracis-28373	336	26	contamination	contamination	NOUN
bracis-28373	336	27	attacks	attack	NOUN
bracis-28373	336	28	against	against	ADP
bracis-28373	336	29	black	black	ADJ
bracis-28373	336	30	-	-	PUNCT
bracis-28373	336	31	box	box	NOUN
bracis-28373	336	32	learning	learning	NOUN
bracis-28373	336	33	models	model	NOUN
bracis-28373	336	34	.	.	PUNCT
bracis-28373	337	1	in	in	ADP
bracis-28373	337	2	:	:	PUNCT
bracis-28373	337	3	proceedings	proceeding	NOUN
bracis-28373	337	4	of	of	ADP
bracis-28373	337	5	the	the	DET
bracis-28373	337	6	twenty	twenty	NUM
bracis-28373	337	7	-	-	PUNCT
bracis-28373	337	8	sixth	sixth	ADJ
bracis-28373	337	9	international	international	ADJ
bracis-28373	337	10	joint	joint	ADJ
bracis-28373	337	11	conference	conference	NOUN
bracis-28373	337	12	on	on	ADP
bracis-28373	337	13	artificial	artificial	ADJ
bracis-28373	337	14	intelligence	intelligence	NOUN
bracis-28373	337	15	(	(	PUNCT
bracis-28373	337	16	ijcai	ijcai	NOUN
bracis-28373	337	17	)	)	PUNCT
bracis-28373	337	18	,	,	PUNCT
bracis-28373	337	19	pp	pp	ADP
bracis-28373	337	20	.	.	PUNCT
bracis-28373	338	1	3945–3951	3945–3951	NUM
bracis-28373	338	2	(	(	PUNCT
bracis-28373	338	3	2017	2017	NUM
bracis-28373	338	4	)	)	PUNCT
bracis-28373	338	5	google	google	PROPN
bracis-28373	338	6	scholar	scholar	NOUN
bracis-28373	338	7	  	  	SPACE
bracis-28373	338	8	download	download	NOUN
bracis-28373	338	9	references	reference	NOUN
bracis-28373	338	10	author	author	NOUN
bracis-28373	338	11	information	information	NOUN
bracis-28373	338	12	authors	author	NOUN
bracis-28373	338	13	and	and	CCONJ
bracis-28373	338	14	affiliations	affiliation	NOUN
bracis-28373	338	15	department	department	PROPN
bracis-28373	338	16	of	of	ADP
bracis-28373	338	17	computer	computer	NOUN
bracis-28373	338	18	science	science	NOUN
bracis-28373	338	19	,	,	PUNCT
bracis-28373	338	20	federal	federal	ADJ
bracis-28373	338	21	university	university	PROPN
bracis-28373	338	22	of	of	ADP
bracis-28373	338	23	minas	minas	PROPN
bracis-28373	338	24	gerais	gerais	PROPN
bracis-28373	338	25	,	,	PUNCT
bracis-28373	338	26	belo	belo	PROPN
bracis-28373	338	27	horizonte	horizonte	PROPN
bracis-28373	338	28	,	,	PUNCT
bracis-28373	338	29	brazil	brazil	PROPN
bracis-28373	338	30	pedro	pedro	PROPN
bracis-28373	338	31	h.	h.	PROPN
bracis-28373	338	32	barros	barros	PROPN
bracis-28373	338	33	 	 	SPACE
bracis-28373	338	34	&	&	CCONJ
bracis-28373	338	35	 	 	SPACE
bracis-28373	338	36	heitor	heitor	PROPN
bracis-28373	338	37	s.	s.	PROPN
bracis-28373	338	38	ramos	ramos	PROPN
bracis-28373	338	39	department	department	PROPN
bracis-28373	338	40	of	of	ADP
bracis-28373	338	41	computer	computer	NOUN
bracis-28373	338	42	science	science	PROPN
bracis-28373	338	43	,	,	PUNCT
bracis-28373	338	44	worcester	worcester	PROPN
bracis-28373	338	45	polytechnic	polytechnic	PROPN
bracis-28373	338	46	institute	institute	PROPN
bracis-28373	338	47	,	,	PUNCT
bracis-28373	338	48	worcester	worcester	PROPN
bracis-28373	338	49	,	,	PUNCT
bracis-28373	338	50	usa	usa	PROPN
bracis-28373	338	51	fabricio	fabricio	PROPN
bracis-28373	338	52	murai	murai	PROPN
bracis-28373	338	53	authors	author	NOUN
bracis-28373	338	54	pedro	pedro	PROPN
bracis-28373	338	55	h.	h.	PROPN
bracis-28373	338	56	barrosview	barrosview	PROPN
bracis-28373	338	57	author	author	NOUN
bracis-28373	338	58	publications	publication	NOUN
bracis-28373	338	59	search	search	NOUN
bracis-28373	338	60	author	author	NOUN
bracis-28373	338	61	on	on	ADP
bracis-28373	338	62	:	:	PUNCT
bracis-28373	338	63	pubmed	pubmed	PROPN
bracis-28373	338	64	 	 	SPACE
bracis-28373	338	65	google	google	PROPN
bracis-28373	338	66	scholar	scholar	PROPN
bracis-28373	338	67	fabricio	fabricio	PROPN
bracis-28373	338	68	muraiview	muraiview	PROPN
bracis-28373	338	69	author	author	NOUN
bracis-28373	338	70	publications	publication	NOUN
bracis-28373	338	71	search	search	NOUN
bracis-28373	338	72	author	author	NOUN
bracis-28373	338	73	on	on	ADP
bracis-28373	338	74	:	:	PUNCT
bracis-28373	338	75	pubmed	pubmed	PROPN
bracis-28373	338	76	 	 	SPACE
bracis-28373	338	77	google	google	PROPN
bracis-28373	338	78	scholar	scholar	NOUN
bracis-28373	338	79	heitor	heitor	PROPN
bracis-28373	338	80	s.	s.	PROPN
bracis-28373	338	81	ramosview	ramosview	PROPN
bracis-28373	338	82	author	author	NOUN
bracis-28373	338	83	publications	publication	VERB
bracis-28373	338	84	search	search	NOUN
bracis-28373	338	85	author	author	NOUN
bracis-28373	338	86	on	on	ADP
bracis-28373	338	87	:	:	PUNCT
bracis-28373	338	88	pubmed	pubmed	PROPN
bracis-28373	338	89	 	 	SPACE
bracis-28373	338	90	google	google	PROPN
bracis-28373	338	91	scholar	scholar	NOUN
bracis-28373	338	92	corresponding	correspond	VERB
bracis-28373	338	93	author	author	NOUN
bracis-28373	338	94	correspondence	correspondence	NOUN
bracis-28373	338	95	to	to	ADP
bracis-28373	338	96	pedro	pedro	PROPN
bracis-28373	338	97	h.	h.	PROPN
bracis-28373	338	98	barros	barros	PROPN
bracis-28373	338	99	.	.	PUNCT
bracis-28373	339	1	editor	editor	NOUN
bracis-28373	339	2	information	information	NOUN
bracis-28373	339	3	editors	editor	NOUN
bracis-28373	339	4	and	and	CCONJ
bracis-28373	339	5	affiliations	affiliation	NOUN
bracis-28373	339	6	federal	federal	PROPN
bracis-28373	339	7	university	university	PROPN
bracis-28373	339	8	of	of	ADP
bracis-28373	339	9	são	são	PROPN
bracis-28373	339	10	carlos	carlos	PROPN
bracis-28373	339	11	,	,	PUNCT
bracis-28373	339	12	são	são	PROPN
bracis-28373	339	13	carlos	carlos	PROPN
bracis-28373	339	14	,	,	PUNCT
bracis-28373	339	15	brazil	brazil	PROPN
bracis-28373	339	16	murilo	murilo	PROPN
bracis-28373	339	17	c.	c.	PROPN
bracis-28373	339	18	naldi	naldi	PROPN
bracis-28373	339	19	centro	centro	PROPN
bracis-28373	339	20	universitario	universitario	PROPN
bracis-28373	339	21	da	da	PROPN
bracis-28373	339	22	fei	fei	PROPN
bracis-28373	339	23	,	,	PUNCT
bracis-28373	339	24	são	são	PROPN
bracis-28373	339	25	bernardo	bernardo	PROPN
bracis-28373	339	26	do	do	AUX
bracis-28373	339	27	campo	campo	PROPN
bracis-28373	339	28	,	,	PUNCT
bracis-28373	339	29	brazil	brazil	PROPN
bracis-28373	339	30	reinaldo	reinaldo	PROPN
bracis-28373	339	31	a.	a.	PROPN
bracis-28373	339	32	c.	c.	PROPN
bracis-28373	339	33	bianchi	bianchi	PROPN
bracis-28373	339	34	rights	right	NOUN
bracis-28373	339	35	and	and	CCONJ
bracis-28373	339	36	permissions	permission	NOUN
bracis-28373	339	37	reprints	reprint	NOUN
bracis-28373	339	38	and	and	CCONJ
bracis-28373	339	39	permissions	permission	VERB
bracis-28373	339	40	copyright	copyright	NOUN
bracis-28373	339	41	information	information	NOUN
bracis-28373	339	42	©	©	ADP
bracis-28373	339	43	2023	2023	NUM
bracis-28373	339	44	the	the	DET
bracis-28373	339	45	author(s	author(s	NOUN
bracis-28373	339	46	)	)	PUNCT
bracis-28373	339	47	,	,	PUNCT
bracis-28373	339	48	under	under	ADP
bracis-28373	339	49	exclusive	exclusive	ADJ
bracis-28373	339	50	license	license	NOUN
bracis-28373	339	51	to	to	ADP
bracis-28373	339	52	springer	springer	NOUN
bracis-28373	339	53	nature	nature	PROPN
bracis-28373	339	54	switzerland	switzerland	PROPN
bracis-28373	339	55	ag	ag	PROPN
bracis-28373	339	56	about	about	ADP
bracis-28373	339	57	this	this	DET
bracis-28373	339	58	paper	paper	NOUN
bracis-28373	339	59	cite	cite	VERB
bracis-28373	339	60	this	this	DET
bracis-28373	339	61	paper	paper	NOUN
bracis-28373	339	62	barros	barros	PROPN
bracis-28373	339	63	,	,	PUNCT
bracis-28373	339	64	p.h	p.h	PROPN
bracis-28373	339	65	.	.	PROPN
bracis-28373	339	66	,	,	PUNCT
bracis-28373	339	67	murai	murai	PROPN
bracis-28373	339	68	,	,	PUNCT
bracis-28373	339	69	f.	f.	PROPN
bracis-28373	339	70	,	,	PUNCT
bracis-28373	339	71	ramos	ramos	PROPN
bracis-28373	339	72	,	,	PUNCT
bracis-28373	339	73	h.s	h.s	PROPN
bracis-28373	339	74	.	.	PROPN
bracis-28373	339	75	(	(	PUNCT
bracis-28373	339	76	2023	2023	NUM
bracis-28373	339	77	)	)	PUNCT
bracis-28373	339	78	.	.	PUNCT
bracis-28373	340	1	bayes	bayes	PROPN
bracis-28373	340	2	and	and	CCONJ
bracis-28373	340	3	 	 	SPACE
bracis-28373	340	4	laplace	laplace	NOUN
bracis-28373	340	5	versus	versus	ADP
bracis-28373	340	6	the	the	DET
bracis-28373	340	7	 	 	SPACE
bracis-28373	340	8	world	world	NOUN
bracis-28373	340	9	:	:	PUNCT
bracis-28373	340	10	a	a	DET
bracis-28373	340	11	new	new	ADJ
bracis-28373	340	12	label	label	NOUN
bracis-28373	340	13	attack	attack	NOUN
bracis-28373	340	14	approach	approach	NOUN
bracis-28373	340	15	in	in	ADP
bracis-28373	340	16	 	 	SPACE
bracis-28373	340	17	federated	federated	ADJ
bracis-28373	340	18	environments	environment	NOUN
bracis-28373	340	19	based	base	VERB
bracis-28373	340	20	on	on	ADP
bracis-28373	340	21	 	 	SPACE
bracis-28373	340	22	bayesian	bayesian	NOUN
bracis-28373	340	23	neural	neural	ADJ
bracis-28373	340	24	networks	network	NOUN
bracis-28373	340	25	.	.	PUNCT
bracis-28373	341	1	in	in	ADP
bracis-28373	341	2	:	:	PUNCT
bracis-28373	341	3	naldi	naldi	PROPN
bracis-28373	341	4	,	,	PUNCT
bracis-28373	341	5	m.c	m.c	PROPN
bracis-28373	341	6	.	.	PROPN
bracis-28373	341	7	,	,	PUNCT
bracis-28373	341	8	bianchi	bianchi	PROPN
bracis-28373	341	9	,	,	PUNCT
bracis-28373	341	10	r.a.c	r.a.c	ADP
bracis-28373	341	11	.	.	PUNCT
bracis-28373	341	12	(	(	PUNCT
bracis-28373	341	13	eds	ed	NOUN
bracis-28373	341	14	)	)	PUNCT
bracis-28373	341	15	intelligent	intelligent	ADJ
bracis-28373	341	16	systems	system	NOUN
bracis-28373	341	17	.	.	PUNCT
bracis-28373	342	1	bracis	bracis	PROPN
bracis-28373	342	2	2023	2023	NUM
bracis-28373	342	3	.	.	PUNCT
bracis-28373	343	1	lecture	lecture	NOUN
bracis-28373	343	2	notes	note	NOUN
bracis-28373	343	3	in	in	ADP
bracis-28373	343	4	computer	computer	NOUN
bracis-28373	343	5	science	science	NOUN
bracis-28373	343	6	(	(	PUNCT
bracis-28373	343	7	)	)	PUNCT
bracis-28373	343	8	,	,	PUNCT
bracis-28373	343	9	vol	vol	NOUN
bracis-28373	343	10	14195	14195	NUM
bracis-28373	343	11	.	.	PUNCT
bracis-28373	344	1	springer	springer	NOUN
bracis-28373	344	2	,	,	PUNCT
bracis-28373	344	3	cham	cham	PROPN
bracis-28373	344	4	.	.	PUNCT
bracis-28373	345	1	https://doi.org/10.1007/978-3-031-45368-7_29	https://doi.org/10.1007/978-3-031-45368-7_29	PROPN
bracis-28373	345	2	download	download	NOUN
bracis-28373	345	3	citation	citation	NOUN
bracis-28373	345	4	.ris	.ris	PUNCT
bracis-28373	346	1	.enw	.enw	PROPN
bracis-28373	346	2	.bib	.bib	PUNCT
bracis-28373	347	1	doi	doi	PROPN
bracis-28373	347	2	:	:	PUNCT
bracis-28373	347	3	https://doi.org/10.1007/978-3-031-45368-7_29	https://doi.org/10.1007/978-3-031-45368-7_29	AUX
bracis-28373	347	4	published	publish	VERB
bracis-28373	347	5	:	:	PUNCT
bracis-28373	347	6	12	12	NUM
bracis-28373	347	7	october	october	PROPN
bracis-28373	347	8	2023	2023	NUM
bracis-28373	347	9	publisher	publisher	NOUN
bracis-28373	347	10	name	name	NOUN
bracis-28373	347	11	:	:	PUNCT
bracis-28373	347	12	springer	springer	NOUN
bracis-28373	347	13	,	,	PUNCT
bracis-28373	347	14	cham	cham	PROPN
bracis-28373	347	15	print	print	PROPN
bracis-28373	347	16	isbn	isbn	PROPN
bracis-28373	347	17	:	:	PUNCT
bracis-28373	347	18	978	978	NUM
bracis-28373	347	19	-	-	SYM
bracis-28373	347	20	3	3	NUM
bracis-28373	347	21	-	-	PUNCT
bracis-28373	347	22	031	031	NUM
bracis-28373	347	23	-	-	PUNCT
bracis-28373	347	24	45367	45367	NUM
bracis-28373	347	25	-	-	PUNCT
bracis-28373	347	26	0	0	NUM
bracis-28373	347	27	online	online	ADJ
bracis-28373	347	28	isbn	isbn	NOUN
bracis-28373	347	29	:	:	PUNCT
bracis-28373	347	30	978	978	NUM
bracis-28373	347	31	-	-	SYM
bracis-28373	347	32	3	3	NUM
bracis-28373	347	33	-	-	PUNCT
bracis-28373	347	34	031	031	NUM
bracis-28373	347	35	-	-	PUNCT
bracis-28373	347	36	45368	45368	NUM
bracis-28373	347	37	-	-	PUNCT
bracis-28373	347	38	7	7	NUM
bracis-28373	347	39	ebook	ebook	NOUN
bracis-28373	347	40	packages	package	NOUN
bracis-28373	347	41	:	:	PUNCT
bracis-28373	347	42	computer	computer	NOUN
bracis-28373	347	43	sciencecomputer	sciencecomputer	NOUN
bracis-28373	347	44	science	science	NOUN
bracis-28373	347	45	(	(	PUNCT
bracis-28373	347	46	r0	r0	NOUN
bracis-28373	347	47	)	)	PUNCT
bracis-28373	347	48	share	share	VERB
bracis-28373	347	49	this	this	DET
bracis-28373	347	50	paper	paper	NOUN
bracis-28373	347	51	anyone	anyone	PRON
bracis-28373	347	52	you	you	PRON
bracis-28373	347	53	share	share	VERB
bracis-28373	347	54	the	the	DET
bracis-28373	347	55	following	follow	VERB
bracis-28373	347	56	link	link	NOUN
bracis-28373	347	57	with	with	ADP
bracis-28373	347	58	will	will	AUX
bracis-28373	347	59	be	be	AUX
bracis-28373	347	60	able	able	ADJ
bracis-28373	347	61	to	to	PART
bracis-28373	347	62	read	read	VERB
bracis-28373	347	63	this	this	DET
bracis-28373	347	64	content	content	NOUN
bracis-28373	347	65	:	:	PUNCT
bracis-28373	347	66	get	get	VERB
bracis-28373	347	67	shareable	shareable	ADJ
bracis-28373	347	68	linksorry	linksorry	NOUN
bracis-28373	347	69	,	,	PUNCT
bracis-28373	347	70	a	a	DET
bracis-28373	347	71	shareable	shareable	ADJ
bracis-28373	347	72	link	link	NOUN
bracis-28373	347	73	is	be	AUX
bracis-28373	347	74	not	not	PART
bracis-28373	347	75	currently	currently	ADV
bracis-28373	347	76	available	available	ADJ
bracis-28373	347	77	for	for	ADP
bracis-28373	347	78	this	this	DET
bracis-28373	347	79	article	article	NOUN
bracis-28373	347	80	.	.	PUNCT
bracis-28373	348	1	copy	copy	VERB
bracis-28373	348	2	shareable	shareable	ADJ
bracis-28373	348	3	link	link	NOUN
bracis-28373	348	4	to	to	PART
bracis-28373	348	5	clipboard	clipboard	NOUN
bracis-28373	348	6	provided	provide	VERB
bracis-28373	348	7	by	by	ADP
bracis-28373	348	8	the	the	DET
bracis-28373	348	9	springer	springer	NOUN
bracis-28373	348	10	nature	nature	PROPN
bracis-28373	348	11	sharedit	sharedit	PROPN
bracis-28373	348	12	content	content	NOUN
bracis-28373	348	13	-	-	PUNCT
bracis-28373	348	14	sharing	share	VERB
bracis-28373	348	15	initiative	initiative	NOUN
bracis-28373	348	16	keywords	keyword	NOUN
bracis-28373	348	17	federated	federate	VERB
bracis-28373	348	18	learning	learn	VERB
bracis-28373	348	19	model	model	NOUN
bracis-28373	348	20	attack	attack	NOUN
bracis-28373	348	21	bayesian	bayesian	NOUN
bracis-28373	348	22	neural	neural	ADJ
bracis-28373	348	23	network	network	NOUN
bracis-28373	348	24	publish	publish	VERB
bracis-28373	348	25	with	with	ADP
bracis-28373	348	26	us	us	PROPN
bracis-28373	348	27	policies	policy	NOUN
bracis-28373	348	28	and	and	CCONJ
bracis-28373	348	29	ethics	ethic	NOUN
bracis-28373	348	30	profiles	profile	NOUN
bracis-28373	348	31	pedro	pedro	PROPN
bracis-28373	348	32	h.	h.	PROPN
bracis-28373	348	33	barros	barros	PROPN
bracis-28373	349	1	view	view	PROPN
bracis-28373	349	2	author	author	NOUN
bracis-28373	349	3	profile	profile	NOUN
bracis-28373	349	4	search	search	NOUN
bracis-28373	349	5	search	search	NOUN
bracis-28373	349	6	by	by	ADP
bracis-28373	349	7	keyword	keyword	NOUN
bracis-28373	349	8	or	or	CCONJ
bracis-28373	349	9	author	author	NOUN
bracis-28373	349	10	search	search	NOUN
bracis-28373	349	11	navigation	navigation	NOUN
bracis-28373	349	12	find	find	VERB
bracis-28373	349	13	a	a	DET
bracis-28373	349	14	journal	journal	NOUN
bracis-28373	349	15	publish	publish	VERB
bracis-28373	349	16	with	with	ADP
bracis-28373	349	17	us	we	PRON
bracis-28373	349	18	track	track	VERB
bracis-28373	349	19	your	your	PRON
bracis-28373	349	20	research	research	NOUN
bracis-28373	349	21	discover	discover	VERB
bracis-28373	349	22	content	content	NOUN
bracis-28373	349	23	journals	journal	NOUN
bracis-28373	349	24	a	a	DET
bracis-28373	349	25	-	-	PUNCT
bracis-28373	349	26	z	z	NOUN
bracis-28373	349	27	books	book	NOUN
bracis-28373	349	28	a	a	DET
bracis-28373	349	29	-	-	PUNCT
bracis-28373	349	30	z	z	NOUN
bracis-28373	349	31	publish	publish	NOUN
bracis-28373	349	32	with	with	ADP
bracis-28373	349	33	us	us	PROPN
bracis-28373	349	34	journal	journal	PROPN
bracis-28373	349	35	finder	finder	PROPN
bracis-28373	349	36	publish	publish	VERB
bracis-28373	349	37	your	your	PRON
bracis-28373	349	38	research	research	NOUN
bracis-28373	349	39	language	language	NOUN
bracis-28373	349	40	editing	edit	VERB
bracis-28373	349	41	open	open	ADJ
bracis-28373	349	42	access	access	NOUN
bracis-28373	349	43	publishing	publishing	NOUN
bracis-28373	349	44	products	product	NOUN
bracis-28373	349	45	and	and	CCONJ
bracis-28373	349	46	services	service	NOUN
bracis-28373	349	47	our	our	PRON
bracis-28373	349	48	products	product	NOUN
bracis-28373	349	49	librarians	librarian	VERB
bracis-28373	349	50	societies	society	NOUN
bracis-28373	349	51	partners	partner	NOUN
bracis-28373	349	52	and	and	CCONJ
bracis-28373	349	53	advertisers	advertiser	NOUN
bracis-28373	349	54	our	our	PRON
bracis-28373	349	55	brands	brand	NOUN
bracis-28373	349	56	springer	springer	NOUN
bracis-28373	349	57	nature	nature	PROPN
bracis-28373	349	58	portfolio	portfolio	PROPN
bracis-28373	349	59	bmc	bmc	PROPN
bracis-28373	349	60	palgrave	palgrave	PROPN
bracis-28373	349	61	macmillan	macmillan	PROPN
bracis-28373	349	62	apress	apress	PROPN
bracis-28373	349	63	discover	discover	VERB
bracis-28373	349	64	your	your	PRON
bracis-28373	349	65	privacy	privacy	NOUN
bracis-28373	349	66	choices	choice	NOUN
bracis-28373	349	67	/	/	SYM
bracis-28373	349	68	manage	manage	NOUN
bracis-28373	349	69	cookies	cookie	NOUN
bracis-28373	349	70	your	your	PRON
bracis-28373	349	71	us	us	PROPN
bracis-28373	350	1	state	state	NOUN
bracis-28373	350	2	privacy	privacy	NOUN
bracis-28373	350	3	rights	right	NOUN
bracis-28373	350	4	accessibility	accessibility	NOUN
bracis-28373	350	5	statement	statement	NOUN
bracis-28373	350	6	terms	term	NOUN
bracis-28373	350	7	and	and	CCONJ
bracis-28373	350	8	conditions	condition	NOUN
bracis-28373	350	9	privacy	privacy	NOUN
bracis-28373	350	10	policy	policy	NOUN
bracis-28373	350	11	help	help	NOUN
bracis-28373	350	12	and	and	CCONJ
bracis-28373	350	13	support	support	VERB
bracis-28373	350	14	legal	legal	ADJ
bracis-28373	350	15	notice	notice	NOUN
bracis-28373	350	16	cancel	cancel	VERB
bracis-28373	350	17	contracts	contract	NOUN
bracis-28373	350	18	here	here	ADV
bracis-28373	350	19	129.74.145.123	129.74.145.123	NUM
bracis-28373	350	20	hesburgh	hesburgh	PROPN
bracis-28373	350	21	library	library	PROPN
bracis-28373	350	22	er	er	INTJ
bracis-28373	350	23	unit	unit	NOUN
bracis-28373	350	24	(	(	PUNCT
bracis-28373	350	25	3005732405	3005732405	NUM
bracis-28373	350	26	)	)	PUNCT
bracis-28373	350	27	northeast	northeast	ADJ
bracis-28373	350	28	research	research	NOUN
bracis-28373	350	29	libraries	library	NOUN
bracis-28373	350	30	(	(	PUNCT
bracis-28373	350	31	nerl	nerl	PROPN
bracis-28373	350	32	)	)	PUNCT
bracis-28373	350	33	(	(	PUNCT
bracis-28373	350	34	8200828607	8200828607	NUM
bracis-28373	350	35	)	)	PUNCT
bracis-28373	350	36	nerl	nerl	VERB
bracis-28373	350	37	ta	ta	X
bracis-28373	350	38	account	account	NOUN
bracis-28373	350	39	(	(	PUNCT
bracis-28373	350	40	3006206169	3006206169	NUM
bracis-28373	350	41	)	)	PUNCT
bracis-28373	350	42	university	university	NOUN
bracis-28373	350	43	of	of	ADP
bracis-28373	350	44	notre	notre	PROPN
bracis-28373	350	45	dame	dame	PROPN
bracis-28373	350	46	hesburgh	hesburgh	PROPN
bracis-28373	350	47	library	library	NOUN
bracis-28373	350	48	(	(	PUNCT
bracis-28373	350	49	3000184373	3000184373	NUM
bracis-28373	350	50	)	)	PUNCT
bracis-28373	351	1	©	©	ADP
bracis-28373	351	2	2025	2025	NUM
bracis-28373	351	3	springer	springer	NOUN
bracis-28373	351	4	nature	nature	NOUN