id	sid	tid	token	lemma	pos
ajst-22330	1	1	academic	academic	ADJ
ajst-22330	1	2	journal	journal	NOUN
ajst-22330	1	3	of	of	ADP
ajst-22330	1	4	science	science	NOUN
ajst-22330	1	5	and	and	CCONJ
ajst-22330	1	6	technology	technology	NOUN
ajst-22330	1	7	issn	issn	NOUN
ajst-22330	1	8	:	:	PUNCT
ajst-22330	1	9	2771	2771	NUM
ajst-22330	1	10	-	-	SYM
ajst-22330	1	11	3032	3032	NUM
ajst-22330	1	12	|	|	NOUN
ajst-22330	1	13	vol	vol	NOUN
ajst-22330	1	14	.	.	PROPN
ajst-22330	2	1	11	11	NUM
ajst-22330	2	2	,	,	PUNCT
ajst-22330	2	3	no	no	INTJ
ajst-22330	2	4	.	.	NOUN
ajst-22330	2	5	2	2	NUM
ajst-22330	2	6	,	,	PUNCT
ajst-22330	2	7	2024	2024	NUM
ajst-22330	2	8	27	27	NUM
ajst-22330	2	9	a	a	DET
ajst-22330	2	10	survey	survey	NOUN
ajst-22330	2	11	of	of	ADP
ajst-22330	2	12	developments	development	NOUN
ajst-22330	2	13	in	in	ADP
ajst-22330	2	14	federated	federated	ADJ
ajst-22330	2	15	meta‐learning	meta‐learning	PROPN
ajst-22330	2	16	yong	yong	PROPN
ajst-22330	2	17	zhang	zhang	PROPN
ajst-22330	2	18	,	,	PUNCT
ajst-22330	2	19	mingchuan	mingchuan	PROPN
ajst-22330	2	20	zhang	zhang	PROPN
ajst-22330	2	21	henan	henan	PROPN
ajst-22330	2	22	university	university	PROPN
ajst-22330	2	23	of	of	ADP
ajst-22330	2	24	science	science	NOUN
ajst-22330	2	25	and	and	CCONJ
ajst-22330	2	26	technology	technology	NOUN
ajst-22330	2	27	,	,	PUNCT
ajst-22330	2	28	luoyang	luoyang	PROPN
ajst-22330	2	29	471000	471000	NUM
ajst-22330	2	30	,	,	PUNCT
ajst-22330	2	31	china	china	PROPN
ajst-22330	2	32	abstract	abstract	NOUN
ajst-22330	2	33	:	:	PUNCT
ajst-22330	2	34	federated	federate	VERB
ajst-22330	2	35	meta	meta	ADV
ajst-22330	2	36	-	-	PUNCT
ajst-22330	2	37	learning	learning	NOUN
ajst-22330	2	38	is	be	AUX
ajst-22330	2	39	a	a	DET
ajst-22330	2	40	widely	widely	ADV
ajst-22330	2	41	used	use	VERB
ajst-22330	2	42	few	few	ADJ
ajst-22330	2	43	-	-	PUNCT
ajst-22330	2	44	shot	shot	NOUN
ajst-22330	2	45	learning	learning	NOUN
ajst-22330	2	46	method	method	NOUN
ajst-22330	2	47	and	and	CCONJ
ajst-22330	2	48	has	have	VERB
ajst-22330	2	49	a	a	DET
ajst-22330	2	50	very	very	ADV
ajst-22330	2	51	good	good	ADJ
ajst-22330	2	52	development	development	NOUN
ajst-22330	2	53	prospect	prospect	NOUN
ajst-22330	2	54	.	.	PUNCT
ajst-22330	3	1	federated	federate	VERB
ajst-22330	3	2	meta	meta	NOUN
ajst-22330	3	3	-	-	PUNCT
ajst-22330	3	4	learning	learning	NOUN
ajst-22330	3	5	combines	combine	VERB
ajst-22330	3	6	the	the	DET
ajst-22330	3	7	characteristics	characteristic	NOUN
ajst-22330	3	8	of	of	ADP
ajst-22330	3	9	federated	federated	ADJ
ajst-22330	3	10	learning	learning	NOUN
ajst-22330	3	11	and	and	CCONJ
ajst-22330	3	12	meta	meta	NOUN
ajst-22330	3	13	-	-	PUNCT
ajst-22330	3	14	learning	learning	NOUN
ajst-22330	3	15	.	.	PUNCT
ajst-22330	4	1	it	it	PRON
ajst-22330	4	2	can	can	AUX
ajst-22330	4	3	not	not	PART
ajst-22330	4	4	only	only	ADV
ajst-22330	4	5	use	use	VERB
ajst-22330	4	6	the	the	DET
ajst-22330	4	7	data	datum	NOUN
ajst-22330	4	8	of	of	ADP
ajst-22330	4	9	each	each	DET
ajst-22330	4	10	client	client	NOUN
ajst-22330	4	11	while	while	SCONJ
ajst-22330	4	12	protecting	protect	VERB
ajst-22330	4	13	its	its	PRON
ajst-22330	4	14	privacy	privacy	NOUN
ajst-22330	4	15	to	to	ADP
ajst-22330	4	16	a	a	DET
ajst-22330	4	17	certain	certain	ADJ
ajst-22330	4	18	extent	extent	NOUN
ajst-22330	4	19	,	,	PUNCT
ajst-22330	4	20	but	but	CCONJ
ajst-22330	4	21	also	also	ADV
ajst-22330	4	22	solve	solve	VERB
ajst-22330	4	23	the	the	DET
ajst-22330	4	24	problem	problem	NOUN
ajst-22330	4	25	of	of	ADP
ajst-22330	4	26	data	datum	NOUN
ajst-22330	4	27	volume	volume	NOUN
ajst-22330	4	28	that	that	PRON
ajst-22330	4	29	requires	require	VERB
ajst-22330	4	30	a	a	DET
ajst-22330	4	31	large	large	ADJ
ajst-22330	4	32	amount	amount	NOUN
ajst-22330	4	33	of	of	ADP
ajst-22330	4	34	data	datum	NOUN
ajst-22330	4	35	for	for	ADP
ajst-22330	4	36	model	model	NOUN
ajst-22330	4	37	training	training	NOUN
ajst-22330	4	38	in	in	ADP
ajst-22330	4	39	machine	machine	NOUN
ajst-22330	4	40	learning	learning	NOUN
ajst-22330	4	41	.	.	PUNCT
ajst-22330	5	1	with	with	ADP
ajst-22330	5	2	the	the	DET
ajst-22330	5	3	rise	rise	NOUN
ajst-22330	5	4	of	of	ADP
ajst-22330	5	5	big	big	ADJ
ajst-22330	5	6	data	datum	NOUN
ajst-22330	5	7	technology	technology	NOUN
ajst-22330	5	8	and	and	CCONJ
ajst-22330	5	9	edge	edge	NOUN
ajst-22330	5	10	computing	computing	NOUN
ajst-22330	5	11	,	,	PUNCT
ajst-22330	5	12	federated	federate	VERB
ajst-22330	5	13	meta	meta	ADJ
ajst-22330	5	14	-	-	PUNCT
ajst-22330	5	15	learning	learn	VERB
ajst-22330	5	16	technology	technology	NOUN
ajst-22330	5	17	has	have	AUX
ajst-22330	5	18	become	become	VERB
ajst-22330	5	19	a	a	DET
ajst-22330	5	20	research	research	NOUN
ajst-22330	5	21	hotspot	hotspot	NOUN
ajst-22330	5	22	in	in	ADP
ajst-22330	5	23	machine	machine	NOUN
ajst-22330	5	24	learning	learning	NOUN
ajst-22330	5	25	.	.	PUNCT
ajst-22330	6	1	in	in	ADP
ajst-22330	6	2	this	this	DET
ajst-22330	6	3	paper	paper	NOUN
ajst-22330	6	4	,	,	PUNCT
ajst-22330	6	5	we	we	PRON
ajst-22330	6	6	provide	provide	VERB
ajst-22330	6	7	an	an	DET
ajst-22330	6	8	overview	overview	NOUN
ajst-22330	6	9	of	of	ADP
ajst-22330	6	10	the	the	DET
ajst-22330	6	11	development	development	NOUN
ajst-22330	6	12	of	of	ADP
ajst-22330	6	13	federated	federated	ADJ
ajst-22330	6	14	meta	meta	ADV
ajst-22330	6	15	-	-	PUNCT
ajst-22330	6	16	learning	learning	NOUN
ajst-22330	6	17	and	and	CCONJ
ajst-22330	6	18	point	point	VERB
ajst-22330	6	19	out	out	ADP
ajst-22330	6	20	the	the	DET
ajst-22330	6	21	relationship	relationship	NOUN
ajst-22330	6	22	between	between	ADP
ajst-22330	6	23	federated	federated	ADJ
ajst-22330	6	24	learning	learning	NOUN
ajst-22330	6	25	,	,	PUNCT
ajst-22330	6	26	meta	meta	ADJ
ajst-22330	6	27	-	-	PUNCT
ajst-22330	6	28	learning	learn	VERB
ajst-22330	6	29	and	and	CCONJ
ajst-22330	6	30	federated	federated	ADJ
ajst-22330	6	31	learning	learning	NOUN
ajst-22330	6	32	.	.	PUNCT
ajst-22330	7	1	finally	finally	ADV
ajst-22330	7	2	,	,	PUNCT
ajst-22330	7	3	some	some	DET
ajst-22330	7	4	existing	exist	VERB
ajst-22330	7	5	problems	problem	NOUN
ajst-22330	7	6	in	in	ADP
ajst-22330	7	7	federated	federated	ADJ
ajst-22330	7	8	meta	meta	NOUN
ajst-22330	7	9	-	-	PUNCT
ajst-22330	7	10	learning	learning	NOUN
ajst-22330	7	11	are	be	AUX
ajst-22330	7	12	pointed	point	VERB
ajst-22330	7	13	out	out	ADP
ajst-22330	7	14	,	,	PUNCT
ajst-22330	7	15	which	which	PRON
ajst-22330	7	16	provides	provide	VERB
ajst-22330	7	17	ideas	idea	NOUN
ajst-22330	7	18	for	for	ADP
ajst-22330	7	19	the	the	DET
ajst-22330	7	20	subsequent	subsequent	ADJ
ajst-22330	7	21	research	research	NOUN
ajst-22330	7	22	on	on	ADP
ajst-22330	7	23	federated	federate	VERB
ajst-22330	7	24	meta	meta	NOUN
ajst-22330	7	25	-	-	PUNCT
ajst-22330	7	26	learning	learning	NOUN
ajst-22330	7	27	.	.	PUNCT
ajst-22330	8	1	keywords	keyword	NOUN
ajst-22330	8	2	:	:	PUNCT
ajst-22330	8	3	federated	federated	ADJ
ajst-22330	8	4	learning	learning	NOUN
ajst-22330	8	5	;	;	PUNCT
ajst-22330	8	6	meta	meta	X
ajst-22330	8	7	-	-	PUNCT
ajst-22330	8	8	learning	learning	NOUN
ajst-22330	8	9	;	;	PUNCT
ajst-22330	8	10	federated	federate	VERB
ajst-22330	8	11	meta	meta	NOUN
ajst-22330	8	12	-	-	PUNCT
ajst-22330	8	13	learning	learning	NOUN
ajst-22330	8	14	.	.	PUNCT
ajst-22330	9	1	1	1	X
ajst-22330	9	2	.	.	X
ajst-22330	9	3	introduction	introduction	NOUN
ajst-22330	9	4	in	in	ADP
ajst-22330	9	5	recent	recent	ADJ
ajst-22330	9	6	years	year	NOUN
ajst-22330	9	7	,	,	PUNCT
ajst-22330	9	8	machine	machine	NOUN
ajst-22330	9	9	learning	learning	NOUN
ajst-22330	9	10	has	have	AUX
ajst-22330	9	11	been	be	AUX
ajst-22330	9	12	extremely	extremely	ADV
ajst-22330	9	13	widely	widely	ADV
ajst-22330	9	14	used	use	VERB
ajst-22330	9	15	in	in	ADP
ajst-22330	9	16	many	many	ADJ
ajst-22330	9	17	scientific	scientific	ADJ
ajst-22330	9	18	fields	field	NOUN
ajst-22330	9	19	with	with	ADP
ajst-22330	9	20	the	the	DET
ajst-22330	9	21	continuous	continuous	ADJ
ajst-22330	9	22	development	development	NOUN
ajst-22330	9	23	of	of	ADP
ajst-22330	9	24	artificial	artificial	ADJ
ajst-22330	9	25	intelligence	intelligence	NOUN
ajst-22330	9	26	technology	technology	NOUN
ajst-22330	9	27	.	.	PUNCT
ajst-22330	10	1	language	language	NOUN
ajst-22330	10	2	recognition	recognition	NOUN
ajst-22330	10	3	,	,	PUNCT
ajst-22330	10	4	face	face	NOUN
ajst-22330	10	5	recognition	recognition	NOUN
ajst-22330	10	6	,	,	PUNCT
ajst-22330	10	7	and	and	CCONJ
ajst-22330	10	8	autonomous	autonomous	ADJ
ajst-22330	10	9	driving	driving	NOUN
ajst-22330	10	10	are	be	AUX
ajst-22330	10	11	all	all	PRON
ajst-22330	10	12	used	use	VERB
ajst-22330	10	13	in	in	ADP
ajst-22330	10	14	daily	daily	ADJ
ajst-22330	10	15	life	life	NOUN
ajst-22330	10	16	.	.	PUNCT
ajst-22330	11	1	and	and	CCONJ
ajst-22330	11	2	the	the	DET
ajst-22330	11	3	development	development	NOUN
ajst-22330	11	4	of	of	ADP
ajst-22330	11	5	machine	machine	NOUN
ajst-22330	11	6	learning	learning	NOUN
ajst-22330	11	7	is	be	AUX
ajst-22330	11	8	driving	drive	VERB
ajst-22330	11	9	the	the	DET
ajst-22330	11	10	development	development	NOUN
ajst-22330	11	11	of	of	ADP
ajst-22330	11	12	modern	modern	ADJ
ajst-22330	11	13	science	science	NOUN
ajst-22330	11	14	and	and	CCONJ
ajst-22330	11	15	technology	technology	NOUN
ajst-22330	11	16	.	.	PUNCT
ajst-22330	12	1	some	some	DET
ajst-22330	12	2	scholars	scholar	NOUN
ajst-22330	12	3	have	have	AUX
ajst-22330	12	4	proposed	propose	VERB
ajst-22330	12	5	that	that	SCONJ
ajst-22330	12	6	machine	machine	NOUN
ajst-22330	12	7	learning	learning	NOUN
ajst-22330	12	8	is	be	AUX
ajst-22330	12	9	playing	play	VERB
ajst-22330	12	10	an	an	DET
ajst-22330	12	11	increasingly	increasingly	ADV
ajst-22330	12	12	important	important	ADJ
ajst-22330	12	13	supporting	support	VERB
ajst-22330	12	14	role	role	NOUN
ajst-22330	12	15	in	in	ADP
ajst-22330	12	16	people	people	NOUN
ajst-22330	12	17	's	's	PART
ajst-22330	12	18	daily	daily	ADJ
ajst-22330	12	19	life	life	NOUN
ajst-22330	12	20	and	and	CCONJ
ajst-22330	12	21	scientific	scientific	ADJ
ajst-22330	12	22	research[1	research[1	NOUN
ajst-22330	12	23	]	]	X
ajst-22330	12	24	.	.	PUNCT
ajst-22330	13	1	alphago[2	alphago[2	X
ajst-22330	13	2	]	]	PUNCT
ajst-22330	13	3	,	,	PUNCT
ajst-22330	13	4	which	which	PRON
ajst-22330	13	5	is	be	AUX
ajst-22330	13	6	well	well	ADV
ajst-22330	13	7	known	know	VERB
ajst-22330	13	8	for	for	ADP
ajst-22330	13	9	defeating	defeat	VERB
ajst-22330	13	10	the	the	DET
ajst-22330	13	11	go	go	NOUN
ajst-22330	13	12	world	world	NOUN
ajst-22330	13	13	champion	champion	PROPN
ajst-22330	13	14	,	,	PUNCT
ajst-22330	13	15	lee	lee	PROPN
ajst-22330	13	16	sedol	sedol	NOUN
ajst-22330	13	17	,	,	PUNCT
ajst-22330	13	18	is	be	AUX
ajst-22330	13	19	ago	ago	ADV
ajst-22330	13	20	artificial	artificial	ADJ
ajst-22330	13	21	intelligence	intelligence	NOUN
ajst-22330	13	22	program	program	NOUN
ajst-22330	13	23	developed	develop	VERB
ajst-22330	13	24	by	by	ADP
ajst-22330	13	25	using	use	VERB
ajst-22330	13	26	deep	deep	ADJ
ajst-22330	13	27	learning	learning	NOUN
ajst-22330	13	28	in	in	ADP
ajst-22330	13	29	machine	machine	NOUN
ajst-22330	13	30	learning	learning	NOUN
ajst-22330	13	31	.	.	PUNCT
ajst-22330	14	1	the	the	DET
ajst-22330	14	2	university	university	PROPN
ajst-22330	14	3	of	of	ADP
ajst-22330	14	4	alberta	alberta	PROPN
ajst-22330	14	5	team	team	PROPN
ajst-22330	14	6	's	's	PART
ajst-22330	14	7	deepstack	deepstack	NOUN
ajst-22330	14	8	beat	beat	VERB
ajst-22330	14	9	the	the	DET
ajst-22330	14	10	pros	pro	NOUN
ajst-22330	14	11	in	in	ADP
ajst-22330	14	12	a	a	DET
ajst-22330	14	13	two	two	NUM
ajst-22330	14	14	-	-	PUNCT
ajst-22330	14	15	player	player	NOUN
ajst-22330	14	16	no	no	NOUN
ajst-22330	14	17	-	-	PUNCT
ajst-22330	14	18	limit	limit	NOUN
ajst-22330	14	19	texas	texas	PROPN
ajst-22330	14	20	hold	hold	VERB
ajst-22330	14	21	'em	them	PRON
ajst-22330	14	22	game[3	game[3	ADV
ajst-22330	14	23	]	]	PUNCT
ajst-22330	14	24	.	.	PUNCT
ajst-22330	15	1	in	in	ADP
ajst-22330	15	2	everyday	everyday	ADJ
ajst-22330	15	3	life	life	NOUN
ajst-22330	15	4	,	,	PUNCT
ajst-22330	15	5	the	the	DET
ajst-22330	15	6	development	development	NOUN
ajst-22330	15	7	process	process	NOUN
ajst-22330	15	8	of	of	ADP
ajst-22330	15	9	machine	machine	NOUN
ajst-22330	15	10	learning	learning	NOUN
ajst-22330	15	11	provides	provide	VERB
ajst-22330	15	12	convenience	convenience	NOUN
ajst-22330	15	13	for	for	ADP
ajst-22330	15	14	people	people	NOUN
ajst-22330	15	15	's	's	PART
ajst-22330	15	16	daily	daily	ADJ
ajst-22330	15	17	life	life	NOUN
ajst-22330	15	18	.	.	PUNCT
ajst-22330	16	1	devlin	devlin	NOUN
ajst-22330	16	2	et	et	PROPN
ajst-22330	16	3	al[4	al[4	PROPN
ajst-22330	16	4	]	]	PUNCT
ajst-22330	16	5	.	.	PUNCT
ajst-22330	17	1	proposed	propose	VERB
ajst-22330	17	2	a	a	DET
ajst-22330	17	3	natural	natural	ADJ
ajst-22330	17	4	language	language	NOUN
ajst-22330	17	5	processing	processing	NOUN
ajst-22330	17	6	method	method	NOUN
ajst-22330	17	7	that	that	PRON
ajst-22330	17	8	enables	enable	VERB
ajst-22330	17	9	better	well	ADJ
ajst-22330	17	10	interaction	interaction	NOUN
ajst-22330	17	11	with	with	ADP
ajst-22330	17	12	machines	machine	NOUN
ajst-22330	17	13	.	.	PUNCT
ajst-22330	18	1	the	the	DET
ajst-22330	18	2	current	current	ADJ
ajst-22330	18	3	self	self	NOUN
ajst-22330	18	4	-	-	PUNCT
ajst-22330	18	5	driving	drive	VERB
ajst-22330	18	6	technology	technology	NOUN
ajst-22330	18	7	was	be	AUX
ajst-22330	18	8	implemented	implement	VERB
ajst-22330	18	9	by	by	ADP
ajst-22330	18	10	the	the	DET
ajst-22330	18	11	waymo	waymo	PROPN
ajst-22330	18	12	team[5	team[5	NOUN
ajst-22330	18	13	]	]	PUNCT
ajst-22330	18	14	using	use	VERB
ajst-22330	18	15	machine	machine	NOUN
ajst-22330	18	16	learning	learning	NOUN
ajst-22330	18	17	and	and	CCONJ
ajst-22330	18	18	tested	test	VERB
ajst-22330	18	19	in	in	ADP
ajst-22330	18	20	a	a	DET
ajst-22330	18	21	variety	variety	NOUN
ajst-22330	18	22	of	of	ADP
ajst-22330	18	23	traffic	traffic	NOUN
ajst-22330	18	24	conditions	condition	NOUN
ajst-22330	18	25	.	.	PUNCT
ajst-22330	19	1	these	these	DET
ajst-22330	19	2	examples	example	NOUN
ajst-22330	19	3	fully	fully	ADV
ajst-22330	19	4	show	show	VERB
ajst-22330	19	5	that	that	SCONJ
ajst-22330	19	6	the	the	DET
ajst-22330	19	7	development	development	NOUN
ajst-22330	19	8	process	process	NOUN
ajst-22330	19	9	of	of	ADP
ajst-22330	19	10	machine	machine	NOUN
ajst-22330	19	11	learning	learning	NOUN
ajst-22330	19	12	has	have	AUX
ajst-22330	19	13	facilitated	facilitate	VERB
ajst-22330	19	14	people	people	NOUN
ajst-22330	19	15	's	's	PART
ajst-22330	19	16	lives	life	NOUN
ajst-22330	19	17	and	and	CCONJ
ajst-22330	19	18	promoted	promote	VERB
ajst-22330	19	19	the	the	DET
ajst-22330	19	20	development	development	NOUN
ajst-22330	19	21	of	of	ADP
ajst-22330	19	22	science	science	NOUN
ajst-22330	19	23	and	and	CCONJ
ajst-22330	19	24	technology	technology	NOUN
ajst-22330	19	25	.	.	PUNCT
ajst-22330	20	1	machine	machine	NOUN
ajst-22330	20	2	learning	learning	NOUN
ajst-22330	20	3	has	have	AUX
ajst-22330	20	4	achieved	achieve	VERB
ajst-22330	20	5	success	success	NOUN
ajst-22330	20	6	in	in	ADP
ajst-22330	20	7	many	many	ADJ
ajst-22330	20	8	fields	field	NOUN
ajst-22330	20	9	,	,	PUNCT
ajst-22330	20	10	and	and	CCONJ
ajst-22330	20	11	the	the	DET
ajst-22330	20	12	foundation	foundation	NOUN
ajst-22330	20	13	of	of	ADP
ajst-22330	20	14	these	these	DET
ajst-22330	20	15	successes	success	NOUN
ajst-22330	20	16	is	be	AUX
ajst-22330	20	17	the	the	DET
ajst-22330	20	18	support	support	NOUN
ajst-22330	20	19	of	of	ADP
ajst-22330	20	20	large	large	ADJ
ajst-22330	20	21	amounts	amount	NOUN
ajst-22330	20	22	of	of	ADP
ajst-22330	20	23	data	datum	NOUN
ajst-22330	20	24	.	.	PUNCT
ajst-22330	21	1	but	but	CCONJ
ajst-22330	21	2	with	with	ADP
ajst-22330	21	3	the	the	DET
ajst-22330	21	4	development	development	NOUN
ajst-22330	21	5	of	of	ADP
ajst-22330	21	6	society	society	NOUN
ajst-22330	21	7	,	,	PUNCT
ajst-22330	21	8	people	people	NOUN
ajst-22330	21	9	pay	pay	VERB
ajst-22330	21	10	more	more	ADJ
ajst-22330	21	11	and	and	CCONJ
ajst-22330	21	12	more	more	ADJ
ajst-22330	21	13	attention	attention	NOUN
ajst-22330	21	14	to	to	ADP
ajst-22330	21	15	their	their	PRON
ajst-22330	21	16	privacy	privacy	NOUN
ajst-22330	21	17	.	.	PUNCT
ajst-22330	22	1	since	since	SCONJ
ajst-22330	22	2	data	datum	NOUN
ajst-22330	22	3	often	often	ADV
ajst-22330	22	4	contains	contain	VERB
ajst-22330	22	5	individual	individual	ADJ
ajst-22330	22	6	or	or	CCONJ
ajst-22330	22	7	group	group	NOUN
ajst-22330	22	8	privacy	privacy	NOUN
ajst-22330	22	9	,	,	PUNCT
ajst-22330	22	10	people	people	NOUN
ajst-22330	22	11	do	do	AUX
ajst-22330	22	12	not	not	PART
ajst-22330	22	13	participate	participate	VERB
ajst-22330	22	14	in	in	ADP
ajst-22330	22	15	data	datum	NOUN
ajst-22330	22	16	sharing	share	VERB
ajst-22330	22	17	in	in	ADP
ajst-22330	22	18	most	most	ADJ
ajst-22330	22	19	cases	case	NOUN
ajst-22330	22	20	for	for	ADP
ajst-22330	22	21	privacy	privacy	NOUN
ajst-22330	22	22	protection	protection	NOUN
ajst-22330	22	23	.	.	PUNCT
ajst-22330	23	1	at	at	ADP
ajst-22330	23	2	the	the	DET
ajst-22330	23	3	same	same	ADJ
ajst-22330	23	4	time	time	NOUN
ajst-22330	23	5	,	,	PUNCT
ajst-22330	23	6	due	due	ADP
ajst-22330	23	7	to	to	ADP
ajst-22330	23	8	the	the	DET
ajst-22330	23	9	rise	rise	NOUN
ajst-22330	23	10	of	of	ADP
ajst-22330	23	11	the	the	DET
ajst-22330	23	12	internet	internet	NOUN
ajst-22330	23	13	of	of	ADP
ajst-22330	23	14	things	thing	NOUN
ajst-22330	23	15	and	and	CCONJ
ajst-22330	23	16	edge	edge	NOUN
ajst-22330	23	17	computing	computing	NOUN
ajst-22330	23	18	,	,	PUNCT
ajst-22330	23	19	data	datum	NOUN
ajst-22330	23	20	is	be	AUX
ajst-22330	23	21	distributed	distribute	VERB
ajst-22330	23	22	on	on	ADP
ajst-22330	23	23	different	different	ADJ
ajst-22330	23	24	devices	device	NOUN
ajst-22330	23	25	,	,	PUNCT
ajst-22330	23	26	resulting	result	VERB
ajst-22330	23	27	in	in	ADP
ajst-22330	23	28	the	the	DET
ajst-22330	23	29	problem	problem	NOUN
ajst-22330	23	30	of	of	ADP
ajst-22330	23	31	data	datum	NOUN
ajst-22330	23	32	island	island	NOUN
ajst-22330	23	33	.	.	PUNCT
ajst-22330	24	1	to	to	PART
ajst-22330	24	2	solve	solve	VERB
ajst-22330	24	3	this	this	DET
ajst-22330	24	4	problem	problem	NOUN
ajst-22330	24	5	,	,	PUNCT
ajst-22330	24	6	some	some	DET
ajst-22330	24	7	scholars	scholar	NOUN
ajst-22330	24	8	have	have	AUX
ajst-22330	24	9	proposed	propose	VERB
ajst-22330	24	10	a	a	DET
ajst-22330	24	11	federated	federated	ADJ
ajst-22330	24	12	learning	learn	VERB
ajst-22330	24	13	framework[6	framework[6	NOUN
ajst-22330	24	14	]	]	PUNCT
ajst-22330	24	15	.	.	PUNCT
ajst-22330	25	1	in	in	ADP
ajst-22330	25	2	federated	federated	ADJ
ajst-22330	25	3	learning	learning	NOUN
ajst-22330	25	4	,	,	PUNCT
ajst-22330	25	5	each	each	DET
ajst-22330	25	6	client	client	NOUN
ajst-22330	25	7	trains	train	VERB
ajst-22330	25	8	a	a	DET
ajst-22330	25	9	local	local	ADJ
ajst-22330	25	10	model	model	NOUN
ajst-22330	25	11	using	use	VERB
ajst-22330	25	12	local	local	ADJ
ajst-22330	25	13	data	datum	NOUN
ajst-22330	25	14	and	and	CCONJ
ajst-22330	25	15	sends	send	VERB
ajst-22330	25	16	the	the	DET
ajst-22330	25	17	model	model	NOUN
ajst-22330	25	18	parameters	parameter	NOUN
ajst-22330	25	19	to	to	ADP
ajst-22330	25	20	the	the	DET
ajst-22330	25	21	server	server	NOUN
ajst-22330	25	22	.	.	PUNCT
ajst-22330	26	1	after	after	SCONJ
ajst-22330	26	2	the	the	DET
ajst-22330	26	3	server	server	NOUN
ajst-22330	26	4	obtains	obtain	VERB
ajst-22330	26	5	the	the	DET
ajst-22330	26	6	model	model	NOUN
ajst-22330	26	7	parameters	parameter	NOUN
ajst-22330	26	8	of	of	ADP
ajst-22330	26	9	each	each	DET
ajst-22330	26	10	client	client	NOUN
ajst-22330	26	11	,	,	PUNCT
ajst-22330	26	12	it	it	PRON
ajst-22330	26	13	averages	average	VERB
ajst-22330	26	14	all	all	DET
ajst-22330	26	15	the	the	DET
ajst-22330	26	16	model	model	NOUN
ajst-22330	26	17	parameters	parameter	NOUN
ajst-22330	26	18	and	and	CCONJ
ajst-22330	26	19	sends	send	VERB
ajst-22330	26	20	the	the	DET
ajst-22330	26	21	model	model	NOUN
ajst-22330	26	22	parameters	parameter	NOUN
ajst-22330	26	23	to	to	ADP
ajst-22330	26	24	the	the	DET
ajst-22330	26	25	client	client	NOUN
ajst-22330	26	26	,	,	PUNCT
ajst-22330	26	27	and	and	CCONJ
ajst-22330	26	28	the	the	DET
ajst-22330	26	29	client	client	NOUN
ajst-22330	26	30	uses	use	VERB
ajst-22330	26	31	the	the	DET
ajst-22330	26	32	averaged	averaged	ADJ
ajst-22330	26	33	model	model	NOUN
ajst-22330	26	34	parameters	parameter	NOUN
ajst-22330	26	35	for	for	ADP
ajst-22330	26	36	the	the	DET
ajst-22330	26	37	next	next	ADJ
ajst-22330	26	38	round	round	NOUN
ajst-22330	26	39	of	of	ADP
ajst-22330	26	40	model	model	NOUN
ajst-22330	26	41	update	update	NOUN
ajst-22330	26	42	.	.	PUNCT
ajst-22330	27	1	this	this	DET
ajst-22330	27	2	update	update	NOUN
ajst-22330	27	3	method	method	NOUN
ajst-22330	27	4	can	can	AUX
ajst-22330	27	5	not	not	PART
ajst-22330	27	6	only	only	ADV
ajst-22330	27	7	make	make	VERB
ajst-22330	27	8	better	well	ADJ
ajst-22330	27	9	use	use	NOUN
ajst-22330	27	10	of	of	ADP
ajst-22330	27	11	the	the	DET
ajst-22330	27	12	large	large	ADJ
ajst-22330	27	13	amount	amount	NOUN
ajst-22330	27	14	of	of	ADP
ajst-22330	27	15	distributed	distribute	VERB
ajst-22330	27	16	data	datum	NOUN
ajst-22330	27	17	obtained	obtain	VERB
ajst-22330	27	18	by	by	ADP
ajst-22330	27	19	big	big	ADJ
ajst-22330	27	20	data	datum	NOUN
ajst-22330	27	21	and	and	CCONJ
ajst-22330	27	22	cloud	cloud	NOUN
ajst-22330	27	23	computing	computing	NOUN
ajst-22330	27	24	technology	technology	NOUN
ajst-22330	27	25	,	,	PUNCT
ajst-22330	27	26	but	but	CCONJ
ajst-22330	27	27	also	also	ADV
ajst-22330	27	28	protect	protect	VERB
ajst-22330	27	29	the	the	DET
ajst-22330	27	30	user	user	NOUN
ajst-22330	27	31	's	's	PART
ajst-22330	27	32	privacy	privacy	NOUN
ajst-22330	27	33	to	to	ADP
ajst-22330	27	34	a	a	DET
ajst-22330	27	35	certain	certain	ADJ
ajst-22330	27	36	extent	extent	NOUN
ajst-22330	27	37	while	while	SCONJ
ajst-22330	27	38	using	use	VERB
ajst-22330	27	39	the	the	DET
ajst-22330	27	40	user	user	NOUN
ajst-22330	27	41	's	's	PART
ajst-22330	27	42	local	local	ADJ
ajst-22330	27	43	data	datum	NOUN
ajst-22330	27	44	.	.	PUNCT
ajst-22330	28	1	since	since	SCONJ
ajst-22330	28	2	the	the	DET
ajst-22330	28	3	characteristics	characteristic	NOUN
ajst-22330	28	4	of	of	ADP
ajst-22330	28	5	federated	federated	ADJ
ajst-22330	28	6	learning	learning	NOUN
ajst-22330	28	7	meet	meet	VERB
ajst-22330	28	8	the	the	DET
ajst-22330	28	9	needs	need	NOUN
ajst-22330	28	10	of	of	ADP
ajst-22330	28	11	actual	actual	ADJ
ajst-22330	28	12	production	production	NOUN
ajst-22330	28	13	environment	environment	NOUN
ajst-22330	28	14	,	,	PUNCT
ajst-22330	28	15	this	this	DET
ajst-22330	28	16	method	method	NOUN
ajst-22330	28	17	has	have	AUX
ajst-22330	28	18	received	receive	VERB
ajst-22330	28	19	extensive	extensive	ADJ
ajst-22330	28	20	attention	attention	NOUN
ajst-22330	28	21	after	after	ADP
ajst-22330	28	22	being	be	AUX
ajst-22330	28	23	proposed	propose	VERB
ajst-22330	28	24	.	.	PUNCT
ajst-22330	29	1	2	2	X
ajst-22330	29	2	.	.	X
ajst-22330	29	3	federated	federated	ADJ
ajst-22330	29	4	learning	learn	VERB
ajst-22330	29	5	federated	federated	ADJ
ajst-22330	29	6	learning	learning	NOUN
ajst-22330	29	7	is	be	AUX
ajst-22330	29	8	a	a	DET
ajst-22330	29	9	framework	framework	NOUN
ajst-22330	29	10	first	first	ADV
ajst-22330	29	11	proposed	propose	VERB
ajst-22330	29	12	by	by	ADP
ajst-22330	29	13	mcmahan	mcmahan	PROPN
ajst-22330	29	14	et	et	PROPN
ajst-22330	29	15	al	al	PROPN
ajst-22330	29	16	.	.	PUNCT
ajst-22330	30	1	it	it	PRON
ajst-22330	30	2	mainly	mainly	ADV
ajst-22330	30	3	performs	perform	VERB
ajst-22330	30	4	local	local	ADJ
ajst-22330	30	5	updates	update	NOUN
ajst-22330	30	6	on	on	ADP
ajst-22330	30	7	the	the	DET
ajst-22330	30	8	client	client	NOUN
ajst-22330	30	9	,	,	PUNCT
ajst-22330	30	10	and	and	CCONJ
ajst-22330	30	11	then	then	ADV
ajst-22330	30	12	realizes	realize	VERB
ajst-22330	30	13	a	a	DET
ajst-22330	30	14	flexible	flexible	ADJ
ajst-22330	30	15	and	and	CCONJ
ajst-22330	30	16	efficient	efficient	ADJ
ajst-22330	30	17	training	training	NOUN
ajst-22330	30	18	mode	mode	NOUN
ajst-22330	30	19	,	,	PUNCT
ajst-22330	30	20	but	but	CCONJ
ajst-22330	30	21	does	do	AUX
ajst-22330	30	22	not	not	PART
ajst-22330	30	23	provide	provide	VERB
ajst-22330	30	24	convergence	convergence	NOUN
ajst-22330	30	25	guarantees	guarantee	NOUN
ajst-22330	30	26	for	for	ADP
ajst-22330	30	27	federated	federated	ADJ
ajst-22330	30	28	learning	learning	NOUN
ajst-22330	30	29	in	in	ADP
ajst-22330	30	30	the	the	DET
ajst-22330	30	31	research	research	NOUN
ajst-22330	30	32	.	.	PUNCT
ajst-22330	31	1	since	since	SCONJ
ajst-22330	31	2	federated	federated	ADJ
ajst-22330	31	3	learning	learning	NOUN
ajst-22330	31	4	was	be	AUX
ajst-22330	31	5	proposed	propose	VERB
ajst-22330	31	6	,	,	PUNCT
ajst-22330	31	7	it	it	PRON
ajst-22330	31	8	has	have	AUX
ajst-22330	31	9	attracted	attract	VERB
ajst-22330	31	10	the	the	DET
ajst-22330	31	11	attention	attention	NOUN
ajst-22330	31	12	of	of	ADP
ajst-22330	31	13	many	many	ADJ
ajst-22330	31	14	scholars	scholar	NOUN
ajst-22330	31	15	,	,	PUNCT
ajst-22330	31	16	and	and	CCONJ
ajst-22330	31	17	has	have	AUX
ajst-22330	31	18	been	be	AUX
ajst-22330	31	19	optimized	optimize	VERB
ajst-22330	31	20	in	in	ADP
ajst-22330	31	21	different	different	ADJ
ajst-22330	31	22	aspects	aspect	NOUN
ajst-22330	31	23	.	.	PUNCT
ajst-22330	32	1	later	later	ADV
ajst-22330	32	2	,	,	PUNCT
ajst-22330	32	3	in	in	ADP
ajst-22330	32	4	the	the	DET
ajst-22330	32	5	study	study	NOUN
ajst-22330	32	6	of	of	ADP
ajst-22330	32	7	federated	federated	ADJ
ajst-22330	32	8	learning	learning	NOUN
ajst-22330	32	9	,	,	PUNCT
ajst-22330	32	10	not	not	PART
ajst-22330	32	11	only	only	ADV
ajst-22330	32	12	the	the	DET
ajst-22330	32	13	analysis	analysis	NOUN
ajst-22330	32	14	of	of	ADP
ajst-22330	32	15	convergence	convergence	NOUN
ajst-22330	32	16	rate	rate	NOUN
ajst-22330	32	17	is	be	AUX
ajst-22330	32	18	provided	provide	VERB
ajst-22330	32	19	,	,	PUNCT
ajst-22330	32	20	but	but	CCONJ
ajst-22330	32	21	also	also	ADV
ajst-22330	32	22	the	the	DET
ajst-22330	32	23	federated	federated	ADJ
ajst-22330	32	24	learning	learning	NOUN
ajst-22330	32	25	is	be	AUX
ajst-22330	32	26	optimized	optimize	VERB
ajst-22330	32	27	.	.	PUNCT
ajst-22330	33	1	wang	wang	PROPN
ajst-22330	33	2	et	et	PROPN
ajst-22330	33	3	al[7	al[7	PROPN
ajst-22330	33	4	]	]	PUNCT
ajst-22330	33	5	.	.	PUNCT
ajst-22330	34	1	improved	improve	VERB
ajst-22330	34	2	the	the	DET
ajst-22330	34	3	convergence	convergence	NOUN
ajst-22330	34	4	rate	rate	NOUN
ajst-22330	34	5	of	of	ADP
ajst-22330	34	6	the	the	DET
ajst-22330	34	7	model	model	NOUN
ajst-22330	34	8	in	in	ADP
ajst-22330	34	9	federated	federated	ADJ
ajst-22330	34	10	learning	learning	NOUN
ajst-22330	34	11	by	by	ADP
ajst-22330	34	12	adding	add	VERB
ajst-22330	34	13	momentum	momentum	NOUN
ajst-22330	34	14	to	to	ADP
ajst-22330	34	15	the	the	DET
ajst-22330	34	16	server	server	NOUN
ajst-22330	34	17	.	.	PUNCT
ajst-22330	35	1	khanduri	khanduri	PROPN
ajst-22330	35	2	et	et	PROPN
ajst-22330	35	3	al[8	al[8	PROPN
ajst-22330	35	4	]	]	PUNCT
ajst-22330	35	5	.	.	PUNCT
ajst-22330	36	1	simultaneously	simultaneously	ADV
ajst-22330	36	2	added	add	VERB
ajst-22330	36	3	momentum	momentum	NOUN
ajst-22330	36	4	to	to	ADP
ajst-22330	36	5	the	the	DET
ajst-22330	36	6	central	central	ADJ
ajst-22330	36	7	agent	agent	NOUN
ajst-22330	36	8	and	and	CCONJ
ajst-22330	36	9	the	the	DET
ajst-22330	36	10	edge	edge	NOUN
ajst-22330	36	11	agent	agent	NOUN
ajst-22330	36	12	to	to	PART
ajst-22330	36	13	improve	improve	VERB
ajst-22330	36	14	the	the	DET
ajst-22330	36	15	convergence	convergence	NOUN
ajst-22330	36	16	speed	speed	NOUN
ajst-22330	36	17	.	.	PUNCT
ajst-22330	37	1	gupta	gupta	NOUN
ajst-22330	37	2	et	et	PROPN
ajst-22330	37	3	al[9	al[9	PROPN
ajst-22330	37	4	]	]	PUNCT
ajst-22330	37	5	improved	improve	VERB
ajst-22330	37	6	the	the	DET
ajst-22330	37	7	model	model	NOUN
ajst-22330	37	8	generalization	generalization	NOUN
ajst-22330	37	9	ability	ability	NOUN
ajst-22330	37	10	of	of	ADP
ajst-22330	37	11	federated	federated	ADJ
ajst-22330	37	12	learning	learning	NOUN
ajst-22330	37	13	by	by	ADP
ajst-22330	37	14	combining	combine	VERB
ajst-22330	37	15	federated	federated	ADJ
ajst-22330	37	16	learning	learning	NOUN
ajst-22330	37	17	with	with	ADP
ajst-22330	37	18	game	game	NOUN
ajst-22330	37	19	theory	theory	NOUN
ajst-22330	37	20	to	to	PART
ajst-22330	37	21	learn	learn	VERB
ajst-22330	37	22	causal	causal	ADJ
ajst-22330	37	23	features	feature	NOUN
ajst-22330	37	24	in	in	ADP
ajst-22330	37	25	the	the	DET
ajst-22330	37	26	client	client	NOUN
ajst-22330	37	27	to	to	PART
ajst-22330	37	28	reach	reach	VERB
ajst-22330	37	29	nash	nash	NOUN
ajst-22330	37	30	equilibrium	equilibrium	NOUN
ajst-22330	37	31	at	at	ADP
ajst-22330	37	32	training	training	NOUN
ajst-22330	37	33	time	time	NOUN
ajst-22330	37	34	.	.	PUNCT
ajst-22330	38	1	on	on	ADP
ajst-22330	38	2	the	the	DET
ajst-22330	38	3	other	other	ADJ
ajst-22330	38	4	,	,	PUNCT
ajst-22330	38	5	hand	hand	NOUN
ajst-22330	38	6	,	,	PUNCT
ajst-22330	38	7	yoon	yoon	PROPN
ajst-22330	38	8	et	et	PROPN
ajst-22330	38	9	al[10	al[10	PROPN
ajst-22330	38	10	]	]	PUNCT
ajst-22330	38	11	.	.	PUNCT
ajst-22330	39	1	proposed	propose	VERB
ajst-22330	39	2	a	a	DET
ajst-22330	39	3	fedmix	fedmix	NOUN
ajst-22330	39	4	federated	federate	VERB
ajst-22330	39	5	learning	learn	VERB
ajst-22330	39	6	framework	framework	NOUN
ajst-22330	39	7	to	to	PART
ajst-22330	39	8	improve	improve	VERB
ajst-22330	39	9	the	the	DET
ajst-22330	39	10	generalization	generalization	NOUN
ajst-22330	39	11	ability	ability	NOUN
ajst-22330	39	12	of	of	ADP
ajst-22330	39	13	global	global	ADJ
ajst-22330	39	14	models	model	NOUN
ajst-22330	39	15	by	by	ADP
ajst-22330	39	16	using	use	VERB
ajst-22330	39	17	mixup	mixup	NOUN
ajst-22330	39	18	,	,	PUNCT
ajst-22330	39	19	a	a	DET
ajst-22330	39	20	data	data	NOUN
ajst-22330	39	21	augmentation	augmentation	NOUN
ajst-22330	39	22	technique	technique	NOUN
ajst-22330	39	23	,	,	PUNCT
ajst-22330	39	24	in	in	ADP
ajst-22330	39	25	federated	federated	ADJ
ajst-22330	39	26	learning	learning	NOUN
ajst-22330	39	27	.	.	PUNCT
ajst-22330	40	1	we	we	PRON
ajst-22330	40	2	present	present	VERB
ajst-22330	40	3	the	the	DET
ajst-22330	40	4	federated	federated	ADJ
ajst-22330	40	5	learning	learning	NOUN
ajst-22330	40	6	framework	framework	NOUN
ajst-22330	40	7	diagram	diagram	NOUN
ajst-22330	40	8	in	in	ADP
ajst-22330	40	9	figure	figure	NOUN
ajst-22330	40	10	1	1	NUM
ajst-22330	40	11	.	.	PUNCT
ajst-22330	40	12	figure	figure	NOUN
ajst-22330	40	13	1	1	NUM
ajst-22330	40	14	.	.	PUNCT
ajst-22330	40	15	federated	federated	ADJ
ajst-22330	40	16	learning	learning	NOUN
ajst-22330	40	17	framework	framework	NOUN
ajst-22330	40	18	θ	θ	PROPN
ajst-22330	40	19	θ2	θ2	PROPN
ajst-22330	40	20	θ3	θ3	PROPN
ajst-22330	40	21	θ1	θ1	PROPN
ajst-22330	40	22	θ	θ	PROPN
ajst-22330	40	23	θ	θ	ADP
ajst-22330	40	24	local	local	ADJ
ajst-22330	40	25	model	model	NOUN
ajst-22330	40	26	1	1	NUM
ajst-22330	40	27	local	local	ADJ
ajst-22330	40	28	model	model	NOUN
ajst-22330	40	29	2	2	NUM
ajst-22330	40	30	local	local	ADJ
ajst-22330	40	31	model	model	NOUN
ajst-22330	40	32	3	3	NUM
ajst-22330	40	33	model	model	NOUN
ajst-22330	40	34	28	28	NUM
ajst-22330	40	35	3	3	NUM
ajst-22330	40	36	.	.	PUNCT
ajst-22330	41	1	meta	meta	VERB
ajst-22330	41	2	-	-	PUNCT
ajst-22330	41	3	learning	learn	VERB
ajst-22330	41	4	meta	meta	VERB
ajst-22330	41	5	-	-	PUNCT
ajst-22330	41	6	learning	learning	NOUN
ajst-22330	41	7	was	be	AUX
ajst-22330	41	8	introduced	introduce	VERB
ajst-22330	41	9	in	in	ADP
ajst-22330	41	10	1998	1998	NUM
ajst-22330	41	11	by	by	ADP
ajst-22330	41	12	thrun	thrun	NOUN
ajst-22330	41	13	et	et	NOUN
ajst-22330	41	14	al[11	al[11	PROPN
ajst-22330	41	15	]	]	PUNCT
ajst-22330	41	16	.	.	PUNCT
ajst-22330	42	1	after	after	SCONJ
ajst-22330	42	2	meta	meta	NOUN
ajst-22330	42	3	-	-	PUNCT
ajst-22330	42	4	learning	learning	NOUN
ajst-22330	42	5	was	be	AUX
ajst-22330	42	6	proposed	propose	VERB
ajst-22330	42	7	,	,	PUNCT
ajst-22330	42	8	it	it	PRON
ajst-22330	42	9	attracted	attract	VERB
ajst-22330	42	10	the	the	DET
ajst-22330	42	11	interest	interest	NOUN
ajst-22330	42	12	of	of	ADP
ajst-22330	42	13	many	many	ADJ
ajst-22330	42	14	scholars	scholar	NOUN
ajst-22330	42	15	,	,	PUNCT
ajst-22330	42	16	who	who	PRON
ajst-22330	42	17	optimized	optimize	VERB
ajst-22330	42	18	meta	meta	NOUN
ajst-22330	42	19	-	-	PUNCT
ajst-22330	42	20	learning	learning	NOUN
ajst-22330	42	21	in	in	ADP
ajst-22330	42	22	different	different	ADJ
ajst-22330	42	23	aspects	aspect	NOUN
ajst-22330	42	24	.	.	PUNCT
ajst-22330	43	1	luke	luke	PROPN
ajst-22330	43	2	metz	metz	PROPN
ajst-22330	43	3	et	et	PROPN
ajst-22330	43	4	al[12	al[12	PROPN
ajst-22330	43	5	]	]	PUNCT
ajst-22330	43	6	.	.	PUNCT
ajst-22330	44	1	investigate	investigate	VERB
ajst-22330	44	2	an	an	DET
ajst-22330	44	3	unsupervised	unsupervised	ADJ
ajst-22330	44	4	update	update	NOUN
ajst-22330	44	5	rule	rule	NOUN
ajst-22330	44	6	that	that	PRON
ajst-22330	44	7	can	can	AUX
ajst-22330	44	8	be	be	AUX
ajst-22330	44	9	used	use	VERB
ajst-22330	44	10	between	between	ADP
ajst-22330	44	11	different	different	ADJ
ajst-22330	44	12	tasks	task	NOUN
ajst-22330	44	13	,	,	PUNCT
ajst-22330	44	14	enabling	enable	VERB
ajst-22330	44	15	it	it	PRON
ajst-22330	44	16	to	to	PART
ajst-22330	44	17	generalize	generalize	VERB
ajst-22330	44	18	to	to	ADP
ajst-22330	44	19	different	different	ADJ
ajst-22330	44	20	neural	neural	ADJ
ajst-22330	44	21	network	network	NOUN
ajst-22330	44	22	architectures	architecture	NOUN
ajst-22330	44	23	,	,	PUNCT
ajst-22330	44	24	datasets	dataset	NOUN
ajst-22330	44	25	,	,	PUNCT
ajst-22330	44	26	and	and	CCONJ
ajst-22330	44	27	data	datum	NOUN
ajst-22330	44	28	modalities	modality	NOUN
ajst-22330	44	29	.	.	PUNCT
ajst-22330	45	1	andrychowicz	andrychowicz	ADJ
ajst-22330	45	2	et	et	NOUN
ajst-22330	45	3	al.[13	al.[13	NOUN
ajst-22330	45	4	]	]	PUNCT
ajst-22330	45	5	proposed	propose	VERB
ajst-22330	45	6	the	the	DET
ajst-22330	45	7	use	use	NOUN
ajst-22330	45	8	of	of	ADP
ajst-22330	45	9	gradient	gradient	ADJ
ajst-22330	45	10	descent	descent	NOUN
ajst-22330	45	11	to	to	PART
ajst-22330	45	12	enable	enable	VERB
ajst-22330	45	13	the	the	DET
ajst-22330	45	14	algorithm	algorithm	NOUN
ajst-22330	45	15	to	to	PART
ajst-22330	45	16	learn	learn	VERB
ajst-22330	45	17	by	by	ADP
ajst-22330	45	18	exploiting	exploit	VERB
ajst-22330	45	19	the	the	DET
ajst-22330	45	20	structure	structure	NOUN
ajst-22330	45	21	in	in	ADP
ajst-22330	45	22	the	the	DET
ajst-22330	45	23	problem	problem	NOUN
ajst-22330	45	24	of	of	ADP
ajst-22330	45	25	interest	interest	NOUN
ajst-22330	45	26	in	in	ADP
ajst-22330	45	27	an	an	DET
ajst-22330	45	28	automatic	automatic	ADJ
ajst-22330	45	29	way	way	NOUN
ajst-22330	45	30	.	.	PUNCT
ajst-22330	46	1	finn	finn	PROPN
ajst-22330	46	2	et	et	PROPN
ajst-22330	46	3	al.[14	al.[14	PROPN
ajst-22330	46	4	]	]	PUNCT
ajst-22330	46	5	proposed	propose	VERB
ajst-22330	46	6	model	model	NOUN
ajst-22330	46	7	-	-	PUNCT
ajst-22330	46	8	agnostics	agnostic	NOUN
ajst-22330	46	9	based	base	VERB
ajst-22330	46	10	meta	meta	PROPN
ajst-22330	46	11	-	-	PUNCT
ajst-22330	46	12	learning	learning	NOUN
ajst-22330	46	13	,	,	PUNCT
ajst-22330	46	14	which	which	PRON
ajst-22330	46	15	learns	learn	VERB
ajst-22330	46	16	features	feature	NOUN
ajst-22330	46	17	to	to	PART
ajst-22330	46	18	adapt	adapt	VERB
ajst-22330	46	19	to	to	ADP
ajst-22330	46	20	new	new	ADJ
ajst-22330	46	21	tasks	task	NOUN
ajst-22330	46	22	more	more	ADV
ajst-22330	46	23	easily	easily	ADV
ajst-22330	46	24	.	.	PUNCT
ajst-22330	47	1	at	at	ADP
ajst-22330	47	2	the	the	DET
ajst-22330	47	3	same	same	ADJ
ajst-22330	47	4	time	time	NOUN
ajst-22330	47	5	,	,	PUNCT
ajst-22330	47	6	in	in	ADP
ajst-22330	47	7	order	order	NOUN
ajst-22330	47	8	to	to	PART
ajst-22330	47	9	solve	solve	VERB
ajst-22330	47	10	the	the	DET
ajst-22330	47	11	problem	problem	NOUN
ajst-22330	47	12	of	of	ADP
ajst-22330	47	13	sparse	sparse	ADJ
ajst-22330	47	14	data	datum	NOUN
ajst-22330	47	15	in	in	ADP
ajst-22330	47	16	some	some	DET
ajst-22330	47	17	fields	field	NOUN
ajst-22330	47	18	,	,	PUNCT
ajst-22330	47	19	such	such	ADJ
ajst-22330	47	20	as	as	ADP
ajst-22330	47	21	rare	rare	ADJ
ajst-22330	47	22	diseases	disease	NOUN
ajst-22330	47	23	,	,	PUNCT
ajst-22330	47	24	it	it	PRON
ajst-22330	47	25	is	be	AUX
ajst-22330	47	26	difficult	difficult	ADJ
ajst-22330	47	27	to	to	PART
ajst-22330	47	28	support	support	VERB
ajst-22330	47	29	federated	federated	ADJ
ajst-22330	47	30	learning	learning	NOUN
ajst-22330	47	31	to	to	PART
ajst-22330	47	32	obtain	obtain	VERB
ajst-22330	47	33	a	a	DET
ajst-22330	47	34	good	good	ADJ
ajst-22330	47	35	model	model	NOUN
ajst-22330	47	36	.	.	PUNCT
ajst-22330	48	1	at	at	ADP
ajst-22330	48	2	the	the	DET
ajst-22330	48	3	same	same	ADJ
ajst-22330	48	4	time	time	NOUN
ajst-22330	48	5	,	,	PUNCT
ajst-22330	48	6	in	in	ADP
ajst-22330	48	7	order	order	NOUN
ajst-22330	48	8	to	to	PART
ajst-22330	48	9	make	make	VERB
ajst-22330	48	10	the	the	DET
ajst-22330	48	11	model	model	NOUN
ajst-22330	48	12	have	have	VERB
ajst-22330	48	13	better	well	ADJ
ajst-22330	48	14	personalization	personalization	NOUN
ajst-22330	48	15	ability	ability	NOUN
ajst-22330	48	16	,	,	PUNCT
ajst-22330	48	17	federated	federate	VERB
ajst-22330	48	18	meta	meta	ADJ
ajst-22330	48	19	-	-	PUNCT
ajst-22330	48	20	learning	learn	VERB
ajst-22330	48	21	framework[15	framework[15	NOUN
ajst-22330	48	22	]	]	PUNCT
ajst-22330	48	23	has	have	AUX
ajst-22330	48	24	been	be	AUX
ajst-22330	48	25	proposed	propose	VERB
ajst-22330	48	26	.	.	PUNCT
ajst-22330	49	1	this	this	PRON
ajst-22330	49	2	is	be	AUX
ajst-22330	49	3	an	an	DET
ajst-22330	49	4	optimization	optimization	NOUN
ajst-22330	49	5	algorithm	algorithm	NOUN
ajst-22330	49	6	that	that	PRON
ajst-22330	49	7	incorporates	incorporate	VERB
ajst-22330	49	8	meta	meta	ADV
ajst-22330	49	9	-	-	PUNCT
ajst-22330	49	10	learning	learning	NOUN
ajst-22330	49	11	into	into	ADP
ajst-22330	49	12	federated	federated	ADJ
ajst-22330	49	13	learning	learning	NOUN
ajst-22330	49	14	.	.	PUNCT
ajst-22330	50	1	this	this	DET
ajst-22330	50	2	paper	paper	NOUN
ajst-22330	50	3	mainly	mainly	ADV
ajst-22330	50	4	considers	consider	VERB
ajst-22330	50	5	that	that	SCONJ
ajst-22330	50	6	meta	meta	NOUN
ajst-22330	50	7	-	-	PUNCT
ajst-22330	50	8	learning	learning	NOUN
ajst-22330	50	9	only	only	ADV
ajst-22330	50	10	needs	need	VERB
ajst-22330	50	11	to	to	PART
ajst-22330	50	12	use	use	VERB
ajst-22330	50	13	a	a	DET
ajst-22330	50	14	small	small	ADJ
ajst-22330	50	15	number	number	NOUN
ajst-22330	50	16	of	of	ADP
ajst-22330	50	17	samples	sample	NOUN
ajst-22330	50	18	to	to	PART
ajst-22330	50	19	learn	learn	VERB
ajst-22330	50	20	unknown	unknown	ADJ
ajst-22330	50	21	tasks	task	NOUN
ajst-22330	50	22	quickly	quickly	ADV
ajst-22330	50	23	.	.	PUNCT
ajst-22330	51	1	model	model	ADJ
ajst-22330	51	2	-	-	ADJ
ajst-22330	51	3	agnostic	agnostic	ADJ
ajst-22330	51	4	meta	meta	NOUN
ajst-22330	51	5	-	-	PUNCT
ajst-22330	51	6	learning[16	learning[16	NOUN
ajst-22330	51	7	]	]	X
ajst-22330	51	8	(	(	PUNCT
ajst-22330	51	9	maml	maml	NOUN
ajst-22330	51	10	)	)	PUNCT
ajst-22330	51	11	is	be	AUX
ajst-22330	51	12	one	one	NUM
ajst-22330	51	13	of	of	ADP
ajst-22330	51	14	the	the	DET
ajst-22330	51	15	most	most	ADV
ajst-22330	51	16	popular	popular	ADJ
ajst-22330	51	17	meta	meta	ADJ
ajst-22330	51	18	-	-	PUNCT
ajst-22330	51	19	learning	learn	VERB
ajst-22330	51	20	methods	method	NOUN
ajst-22330	51	21	,	,	PUNCT
ajst-22330	51	22	which	which	PRON
ajst-22330	51	23	can	can	AUX
ajst-22330	51	24	match	match	VERB
ajst-22330	51	25	any	any	DET
ajst-22330	51	26	model	model	NOUN
ajst-22330	51	27	trained	train	VERB
ajst-22330	51	28	using	use	VERB
ajst-22330	51	29	gradient	gradient	ADJ
ajst-22330	51	30	descent	descent	NOUN
ajst-22330	51	31	algorithms	algorithm	NOUN
ajst-22330	51	32	and	and	CCONJ
ajst-22330	51	33	can	can	AUX
ajst-22330	51	34	be	be	AUX
ajst-22330	51	35	applied	apply	VERB
ajst-22330	51	36	to	to	ADP
ajst-22330	51	37	a	a	DET
ajst-22330	51	38	variety	variety	NOUN
ajst-22330	51	39	of	of	ADP
ajst-22330	51	40	different	different	ADJ
ajst-22330	51	41	problems	problem	NOUN
ajst-22330	51	42	,	,	PUNCT
ajst-22330	51	43	such	such	ADJ
ajst-22330	51	44	as	as	ADP
ajst-22330	51	45	classification	classification	NOUN
ajst-22330	51	46	,	,	PUNCT
ajst-22330	51	47	regression	regression	NOUN
ajst-22330	51	48	,	,	PUNCT
ajst-22330	51	49	and	and	CCONJ
ajst-22330	51	50	reinforcement	reinforcement	NOUN
ajst-22330	51	51	learning[14	learning[14	PROPN
ajst-22330	51	52	]	]	PUNCT
ajst-22330	51	53	.	.	PUNCT
ajst-22330	52	1	4	4	X
ajst-22330	52	2	.	.	NUM
ajst-22330	52	3	federated	federate	VERB
ajst-22330	52	4	meta	meta	ADV
ajst-22330	52	5	-	-	PUNCT
ajst-22330	52	6	learning	learn	VERB
ajst-22330	52	7	federated	federated	ADJ
ajst-22330	52	8	learning	learning	NOUN
ajst-22330	52	9	and	and	CCONJ
ajst-22330	52	10	meta	meta	ADV
ajst-22330	52	11	-	-	PUNCT
ajst-22330	52	12	learning	learning	NOUN
ajst-22330	52	13	are	be	AUX
ajst-22330	52	14	both	both	PRON
ajst-22330	52	15	gaining	gain	VERB
ajst-22330	52	16	attention	attention	NOUN
ajst-22330	52	17	because	because	SCONJ
ajst-22330	52	18	their	their	PRON
ajst-22330	52	19	integration	integration	NOUN
ajst-22330	52	20	is	be	AUX
ajst-22330	52	21	an	an	DET
ajst-22330	52	22	inevitable	inevitable	ADJ
ajst-22330	52	23	development	development	NOUN
ajst-22330	52	24	.	.	PUNCT
ajst-22330	53	1	federated	federate	VERB
ajst-22330	53	2	meta	meta	NOUN
ajst-22330	53	3	-	-	PUNCT
ajst-22330	53	4	learning	learning	NOUN
ajst-22330	53	5	,	,	PUNCT
ajst-22330	53	6	which	which	PRON
ajst-22330	53	7	combines	combine	VERB
ajst-22330	53	8	federated	federated	ADJ
ajst-22330	53	9	learning	learning	NOUN
ajst-22330	53	10	and	and	CCONJ
ajst-22330	53	11	meta	meta	NOUN
ajst-22330	53	12	-	-	PUNCT
ajst-22330	53	13	learning	learning	NOUN
ajst-22330	53	14	,	,	PUNCT
ajst-22330	53	15	was	be	AUX
ajst-22330	53	16	first	first	ADV
ajst-22330	53	17	proposed	propose	VERB
ajst-22330	53	18	by	by	ADP
ajst-22330	53	19	chen	chen	PROPN
ajst-22330	53	20	et	et	PROPN
ajst-22330	53	21	al[17	al[17	PROPN
ajst-22330	53	22	]	]	X
ajst-22330	53	23	.	.	PUNCT
ajst-22330	53	24	,	,	PUNCT
ajst-22330	53	25	to	to	PART
ajst-22330	53	26	obtain	obtain	VERB
ajst-22330	53	27	faster	fast	ADJ
ajst-22330	53	28	convergence	convergence	NOUN
ajst-22330	53	29	rate	rate	NOUN
ajst-22330	53	30	and	and	CCONJ
ajst-22330	53	31	higher	high	ADJ
ajst-22330	53	32	accuracy	accuracy	NOUN
ajst-22330	53	33	.	.	PUNCT
ajst-22330	54	1	federated	federate	VERB
ajst-22330	54	2	meta	meta	NOUN
ajst-22330	54	3	-	-	PUNCT
ajst-22330	54	4	learning	learning	NOUN
ajst-22330	54	5	uses	use	VERB
ajst-22330	54	6	maml	maml	PROPN
ajst-22330	54	7	method	method	NOUN
ajst-22330	54	8	to	to	PART
ajst-22330	54	9	train	train	VERB
ajst-22330	54	10	the	the	DET
ajst-22330	54	11	local	local	ADJ
ajst-22330	54	12	meta	meta	ADJ
ajst-22330	54	13	model	model	NOUN
ajst-22330	54	14	on	on	ADP
ajst-22330	54	15	the	the	DET
ajst-22330	54	16	client	client	NOUN
ajst-22330	54	17	,	,	PUNCT
ajst-22330	54	18	and	and	CCONJ
ajst-22330	54	19	then	then	ADV
ajst-22330	54	20	passes	pass	VERB
ajst-22330	54	21	the	the	DET
ajst-22330	54	22	meta	meta	ADJ
ajst-22330	54	23	model	model	NOUN
ajst-22330	54	24	parameters	parameter	NOUN
ajst-22330	54	25	to	to	ADP
ajst-22330	54	26	the	the	DET
ajst-22330	54	27	server	server	NOUN
ajst-22330	54	28	for	for	ADP
ajst-22330	54	29	model	model	NOUN
ajst-22330	54	30	parameter	parameter	PROPN
ajst-22330	54	31	aggregation	aggregation	NOUN
ajst-22330	54	32	.	.	PUNCT
ajst-22330	55	1	the	the	DET
ajst-22330	55	2	server	server	NOUN
ajst-22330	55	3	aggregates	aggregate	VERB
ajst-22330	55	4	the	the	DET
ajst-22330	55	5	model	model	NOUN
ajst-22330	55	6	parameters	parameter	NOUN
ajst-22330	55	7	and	and	CCONJ
ajst-22330	55	8	sends	send	VERB
ajst-22330	55	9	them	they	PRON
ajst-22330	55	10	to	to	ADP
ajst-22330	55	11	the	the	DET
ajst-22330	55	12	client	client	NOUN
ajst-22330	55	13	as	as	ADP
ajst-22330	55	14	the	the	DET
ajst-22330	55	15	initial	initial	ADJ
ajst-22330	55	16	model	model	NOUN
ajst-22330	55	17	parameters	parameter	NOUN
ajst-22330	55	18	for	for	ADP
ajst-22330	55	19	the	the	DET
ajst-22330	55	20	next	next	ADJ
ajst-22330	55	21	update	update	NOUN
ajst-22330	55	22	.	.	PUNCT
ajst-22330	56	1	federated	federate	VERB
ajst-22330	56	2	meta	meta	NOUN
ajst-22330	56	3	-	-	PUNCT
ajst-22330	56	4	learning	learning	NOUN
ajst-22330	56	5	can	can	AUX
ajst-22330	56	6	make	make	VERB
ajst-22330	56	7	use	use	NOUN
ajst-22330	56	8	of	of	ADP
ajst-22330	56	9	data	datum	NOUN
ajst-22330	56	10	distributed	distribute	VERB
ajst-22330	56	11	on	on	ADP
ajst-22330	56	12	different	different	ADJ
ajst-22330	56	13	clients	client	NOUN
ajst-22330	56	14	while	while	SCONJ
ajst-22330	56	15	protecting	protect	VERB
ajst-22330	56	16	its	its	PRON
ajst-22330	56	17	privacy	privacy	NOUN
ajst-22330	56	18	,	,	PUNCT
ajst-22330	56	19	and	and	CCONJ
ajst-22330	56	20	better	well	ADJ
ajst-22330	56	21	train	train	NOUN
ajst-22330	56	22	metamodels	metamodel	NOUN
ajst-22330	56	23	suitable	suitable	ADJ
ajst-22330	56	24	for	for	ADP
ajst-22330	56	25	multiple	multiple	ADJ
ajst-22330	56	26	tasks	task	NOUN
ajst-22330	56	27	.	.	PUNCT
ajst-22330	57	1	it	it	PRON
ajst-22330	57	2	is	be	AUX
ajst-22330	57	3	also	also	ADV
ajst-22330	57	4	possible	possible	ADJ
ajst-22330	57	5	to	to	PART
ajst-22330	57	6	use	use	VERB
ajst-22330	57	7	the	the	DET
ajst-22330	57	8	feature	feature	NOUN
ajst-22330	57	9	of	of	ADP
ajst-22330	57	10	meta	meta	NOUN
ajst-22330	57	11	-	-	PUNCT
ajst-22330	57	12	learning	learning	NOUN
ajst-22330	57	13	to	to	PART
ajst-22330	57	14	quickly	quickly	ADV
ajst-22330	57	15	adapt	adapt	VERB
ajst-22330	57	16	to	to	ADP
ajst-22330	57	17	new	new	ADJ
ajst-22330	57	18	tasks	task	NOUN
ajst-22330	57	19	to	to	PART
ajst-22330	57	20	provide	provide	VERB
ajst-22330	57	21	different	different	ADJ
ajst-22330	57	22	models	model	NOUN
ajst-22330	57	23	for	for	ADP
ajst-22330	57	24	different	different	ADJ
ajst-22330	57	25	users	user	NOUN
ajst-22330	57	26	.	.	PUNCT
ajst-22330	58	1	figure	figure	VERB
ajst-22330	58	2	2	2	NUM
ajst-22330	58	3	.	.	PUNCT
ajst-22330	58	4	federated	federate	VERB
ajst-22330	58	5	meta	meta	ADJ
ajst-22330	58	6	-	-	PUNCT
ajst-22330	58	7	learning	learn	VERB
ajst-22330	58	8	framework	framework	NOUN
ajst-22330	58	9	since	since	SCONJ
ajst-22330	58	10	federated	federate	VERB
ajst-22330	58	11	meta	meta	NOUN
ajst-22330	58	12	-	-	PUNCT
ajst-22330	58	13	learning	learning	NOUN
ajst-22330	58	14	was	be	AUX
ajst-22330	58	15	proposed	propose	VERB
ajst-22330	58	16	,	,	PUNCT
ajst-22330	58	17	the	the	DET
ajst-22330	58	18	combination	combination	NOUN
ajst-22330	58	19	of	of	ADP
ajst-22330	58	20	federated	federated	ADJ
ajst-22330	58	21	learning	learning	NOUN
ajst-22330	58	22	framework	framework	NOUN
ajst-22330	58	23	and	and	CCONJ
ajst-22330	58	24	metalearning	metalearning	NOUN
ajst-22330	58	25	has	have	AUX
ajst-22330	58	26	received	receive	VERB
ajst-22330	58	27	extensive	extensive	ADJ
ajst-22330	58	28	attention	attention	NOUN
ajst-22330	58	29	.	.	PUNCT
ajst-22330	59	1	khodak	khodak	PROPN
ajst-22330	59	2	et	et	PROPN
ajst-22330	60	1	al.[18	al.[18	PROPN
ajst-22330	60	2	]	]	PUNCT
ajst-22330	60	3	proposed	propose	VERB
ajst-22330	60	4	a	a	DET
ajst-22330	60	5	meta	meta	ADV
ajst-22330	60	6	-	-	PUNCT
ajst-22330	60	7	learning	learn	VERB
ajst-22330	60	8	method	method	NOUN
ajst-22330	60	9	with	with	ADP
ajst-22330	60	10	adaptive	adaptive	ADJ
ajst-22330	60	11	learning	learning	NOUN
ajst-22330	60	12	rate	rate	NOUN
ajst-22330	60	13	and	and	CCONJ
ajst-22330	60	14	applied	apply	VERB
ajst-22330	60	15	it	it	PRON
ajst-22330	60	16	to	to	ADP
ajst-22330	60	17	federated	federated	ADJ
ajst-22330	60	18	learning	learning	NOUN
ajst-22330	60	19	.	.	PUNCT
ajst-22330	61	1	fallah	fallah	ADJ
ajst-22330	61	2	et	et	NOUN
ajst-22330	61	3	al.[19	al.[19	PROPN
ajst-22330	61	4	]	]	PUNCT
ajst-22330	61	5	proposed	propose	VERB
ajst-22330	61	6	a	a	DET
ajst-22330	61	7	personalized	personalize	VERB
ajst-22330	61	8	federated	federate	VERB
ajst-22330	61	9	meta	meta	ADJ
ajst-22330	61	10	-	-	PUNCT
ajst-22330	61	11	learning	learn	VERB
ajst-22330	61	12	method	method	NOUN
ajst-22330	61	13	,	,	PUNCT
ajst-22330	61	14	and	and	CCONJ
ajst-22330	61	15	they	they	PRON
ajst-22330	61	16	proposed	propose	VERB
ajst-22330	61	17	an	an	DET
ajst-22330	61	18	algorithm	algorithm	NOUN
ajst-22330	61	19	for	for	SCONJ
ajst-22330	61	20	all	all	DET
ajst-22330	61	21	agents	agent	NOUN
ajst-22330	61	22	to	to	PART
ajst-22330	61	23	share	share	VERB
ajst-22330	61	24	the	the	DET
ajst-22330	61	25	starting	starting	NOUN
ajst-22330	61	26	model	model	NOUN
ajst-22330	61	27	.	.	PUNCT
ajst-22330	62	1	kayaalp	kayaalp	NOUN
ajst-22330	62	2	et	et	NOUN
ajst-22330	62	3	al.[20	al.[20	NOUN
ajst-22330	62	4	]	]	PUNCT
ajst-22330	62	5	study	study	VERB
ajst-22330	62	6	a	a	DET
ajst-22330	62	7	decentralized	decentralize	VERB
ajst-22330	62	8	federated	federate	VERB
ajst-22330	62	9	meta	meta	NOUN
ajst-22330	62	10	-	-	PUNCT
ajst-22330	62	11	learning	learning	NOUN
ajst-22330	62	12	.	.	PUNCT
ajst-22330	63	1	this	this	DET
ajst-22330	63	2	method	method	NOUN
ajst-22330	63	3	can	can	AUX
ajst-22330	63	4	make	make	VERB
ajst-22330	63	5	the	the	DET
ajst-22330	63	6	system	system	NOUN
ajst-22330	63	7	more	more	ADV
ajst-22330	63	8	extensible	extensible	ADJ
ajst-22330	63	9	and	and	CCONJ
ajst-22330	63	10	flexible	flexible	ADJ
ajst-22330	63	11	,	,	PUNCT
ajst-22330	63	12	and	and	CCONJ
ajst-22330	63	13	avoid	avoid	VERB
ajst-22330	63	14	the	the	DET
ajst-22330	63	15	communication	communication	NOUN
ajst-22330	63	16	bottleneck	bottleneck	NOUN
ajst-22330	63	17	in	in	ADP
ajst-22330	63	18	the	the	DET
ajst-22330	63	19	central	central	ADJ
ajst-22330	63	20	processor	processor	NOUN
ajst-22330	63	21	.	.	PUNCT
ajst-22330	64	1	in	in	ADP
ajst-22330	64	2	figure	figure	NOUN
ajst-22330	64	3	2	2	NUM
ajst-22330	64	4	,	,	PUNCT
ajst-22330	64	5	the	the	DET
ajst-22330	64	6	structural	structural	ADJ
ajst-22330	64	7	framework	framework	NOUN
ajst-22330	64	8	of	of	ADP
ajst-22330	64	9	federated	federated	ADJ
ajst-22330	64	10	meta	meta	NOUN
ajst-22330	64	11	-	-	PUNCT
ajst-22330	64	12	learning	learning	NOUN
ajst-22330	64	13	is	be	AUX
ajst-22330	64	14	shown	show	VERB
ajst-22330	64	15	.	.	PUNCT
ajst-22330	65	1	in	in	ADP
ajst-22330	65	2	federated	federated	ADJ
ajst-22330	65	3	learning	learning	NOUN
ajst-22330	65	4	,	,	PUNCT
ajst-22330	65	5	especially	especially	ADV
ajst-22330	65	6	federated	federate	VERB
ajst-22330	65	7	meta	meta	NOUN
ajst-22330	65	8	-	-	PUNCT
ajst-22330	65	9	learning	learning	NOUN
ajst-22330	65	10	,	,	PUNCT
ajst-22330	65	11	the	the	DET
ajst-22330	65	12	generalization	generalization	NOUN
ajst-22330	65	13	ability	ability	NOUN
ajst-22330	65	14	of	of	ADP
ajst-22330	65	15	models	model	NOUN
ajst-22330	65	16	faces	face	VERB
ajst-22330	65	17	more	more	ADJ
ajst-22330	65	18	challenges	challenge	NOUN
ajst-22330	65	19	than	than	ADP
ajst-22330	65	20	the	the	DET
ajst-22330	65	21	generalization	generalization	NOUN
ajst-22330	65	22	ability	ability	NOUN
ajst-22330	65	23	of	of	ADP
ajst-22330	65	24	models	model	NOUN
ajst-22330	65	25	derived	derive	VERB
ajst-22330	65	26	from	from	ADP
ajst-22330	65	27	centralized	centralized	ADJ
ajst-22330	65	28	algorithms	algorithm	NOUN
ajst-22330	65	29	.	.	PUNCT
ajst-22330	66	1	for	for	ADP
ajst-22330	66	2	example	example	NOUN
ajst-22330	66	3	,	,	PUNCT
ajst-22330	66	4	the	the	DET
ajst-22330	66	5	data	datum	NOUN
ajst-22330	66	6	heterogeneity	heterogeneity	PROPN
ajst-22330	66	7	problem	problem	NOUN
ajst-22330	66	8	between	between	ADP
ajst-22330	66	9	different	different	ADJ
ajst-22330	66	10	clients	client	NOUN
ajst-22330	66	11	,	,	PUNCT
ajst-22330	66	12	the	the	DET
ajst-22330	66	13	two	two	NUM
ajst-22330	66	14	-	-	PUNCT
ajst-22330	66	15	layer	layer	NOUN
ajst-22330	66	16	structure	structure	NOUN
ajst-22330	66	17	of	of	ADP
ajst-22330	66	18	federated	federated	ADJ
ajst-22330	66	19	meta	meta	NOUN
ajst-22330	66	20	-	-	PUNCT
ajst-22330	66	21	learning	learning	NOUN
ajst-22330	66	22	leads	lead	VERB
ajst-22330	66	23	to	to	ADP
ajst-22330	66	24	a	a	DET
ajst-22330	66	25	more	more	ADV
ajst-22330	66	26	complex	complex	ADJ
ajst-22330	66	27	loss	loss	NOUN
ajst-22330	66	28	landscape	landscape	NOUN
ajst-22330	66	29	.	.	PUNCT
ajst-22330	67	1	aiming	aim	VERB
ajst-22330	67	2	at	at	ADP
ajst-22330	67	3	the	the	DET
ajst-22330	67	4	generalization	generalization	NOUN
ajst-22330	67	5	problem	problem	NOUN
ajst-22330	67	6	of	of	ADP
ajst-22330	67	7	federated	federated	ADJ
ajst-22330	67	8	learning	learning	NOUN
ajst-22330	67	9	algorithms	algorithm	NOUN
ajst-22330	67	10	with	with	ADP
ajst-22330	67	11	semi	semi	ADJ
ajst-22330	67	12	-	-	ADJ
ajst-22330	67	13	distributed	distributed	ADJ
ajst-22330	67	14	structure	structure	NOUN
ajst-22330	67	15	,	,	PUNCT
ajst-22330	67	16	mendieta	mendieta	PROPN
ajst-22330	67	17	et	et	NOUN
ajst-22330	67	18	al.[21	al.[21	PROPN
ajst-22330	67	19	]	]	PUNCT
ajst-22330	67	20	solved	solve	VERB
ajst-22330	67	21	the	the	DET
ajst-22330	67	22	problem	problem	NOUN
ajst-22330	67	23	of	of	ADP
ajst-22330	67	24	data	datum	NOUN
ajst-22330	67	25	heterogeneity	heterogeneity	NOUN
ajst-22330	67	26	by	by	ADP
ajst-22330	67	27	using	use	VERB
ajst-22330	67	28	standard	standard	ADJ
ajst-22330	67	29	regularization	regularization	NOUN
ajst-22330	67	30	techniques	technique	NOUN
ajst-22330	67	31	.	.	PUNCT
ajst-22330	68	1	caldarola	caldarola	PROPN
ajst-22330	68	2	et	et	PROPN
ajst-22330	68	3	al.[22	al.[22	PROPN
ajst-22330	68	4	]	]	PUNCT
ajst-22330	68	5	used	use	VERB
ajst-22330	68	6	experiments	experiment	NOUN
ajst-22330	68	7	to	to	PART
ajst-22330	68	8	verify	verify	VERB
ajst-22330	68	9	that	that	DET
ajst-22330	68	10	sharpness	sharpness	NOUN
ajst-22330	68	11	aware	aware	ADJ
ajst-22330	68	12	minimization	minimization	NOUN
ajst-22330	68	13	can	can	AUX
ajst-22330	68	14	be	be	AUX
ajst-22330	68	15	used	use	VERB
ajst-22330	68	16	as	as	ADP
ajst-22330	68	17	a	a	DET
ajst-22330	68	18	local	local	ADJ
ajst-22330	68	19	optimizer	optimizer	NOUN
ajst-22330	68	20	to	to	PART
ajst-22330	68	21	improve	improve	VERB
ajst-22330	68	22	the	the	DET
ajst-22330	68	23	generalization	generalization	NOUN
ajst-22330	68	24	ability	ability	NOUN
ajst-22330	68	25	of	of	ADP
ajst-22330	68	26	federated	federated	ADJ
ajst-22330	68	27	learning	learning	NOUN
ajst-22330	68	28	.	.	PUNCT
ajst-22330	69	1	since	since	SCONJ
ajst-22330	69	2	it	it	PRON
ajst-22330	69	3	has	have	AUX
ajst-22330	69	4	been	be	AUX
ajst-22330	69	5	proved	prove	VERB
ajst-22330	69	6	that	that	SCONJ
ajst-22330	69	7	sharp	sharp	ADJ
ajst-22330	69	8	minima	minima	NOUN
ajst-22330	69	9	will	will	AUX
ajst-22330	69	10	have	have	VERB
ajst-22330	69	11	a	a	DET
ajst-22330	69	12	significant	significant	ADJ
ajst-22330	69	13	impact	impact	NOUN
ajst-22330	69	14	on	on	ADP
ajst-22330	69	15	the	the	DET
ajst-22330	69	16	generalization	generalization	NOUN
ajst-22330	69	17	ability	ability	NOUN
ajst-22330	69	18	of	of	ADP
ajst-22330	69	19	the	the	DET
ajst-22330	69	20	model	model	NOUN
ajst-22330	69	21	.	.	PUNCT
ajst-22330	70	1	in	in	ADP
ajst-22330	70	2	order	order	NOUN
ajst-22330	70	3	to	to	PART
ajst-22330	70	4	avoid	avoid	VERB
ajst-22330	70	5	finding	find	VERB
ajst-22330	70	6	sharp	sharp	ADJ
ajst-22330	70	7	minima	minima	NOUN
ajst-22330	70	8	when	when	SCONJ
ajst-22330	70	9	the	the	DET
ajst-22330	70	10	model	model	NOUN
ajst-22330	70	11	converges	converge	VERB
ajst-22330	70	12	,	,	PUNCT
ajst-22330	70	13	the	the	DET
ajst-22330	70	14	generalization	generalization	NOUN
ajst-22330	70	15	ability	ability	NOUN
ajst-22330	70	16	of	of	ADP
ajst-22330	70	17	the	the	DET
ajst-22330	70	18	model	model	NOUN
ajst-22330	70	19	is	be	AUX
ajst-22330	70	20	improved	improve	VERB
ajst-22330	70	21	by	by	ADP
ajst-22330	70	22	starting	start	VERB
ajst-22330	70	23	from	from	ADP
ajst-22330	70	24	the	the	DET
ajst-22330	70	25	sharp	sharp	ADJ
ajst-22330	70	26	points	point	NOUN
ajst-22330	70	27	of	of	ADP
ajst-22330	70	28	the	the	DET
ajst-22330	70	29	model	model	NOUN
ajst-22330	70	30	.	.	PUNCT
ajst-22330	71	1	chaudhari	chaudhari	PROPN
ajst-22330	71	2	et	et	PROPN
ajst-22330	71	3	al.[23]proposed	al.[23]propose	VERB
ajst-22330	71	4	an	an	DET
ajst-22330	71	5	entropysgd	entropysgd	NOUN
ajst-22330	71	6	algorithm	algorithm	NOUN
ajst-22330	71	7	,	,	PUNCT
ajst-22330	71	8	which	which	PRON
ajst-22330	71	9	uses	use	VERB
ajst-22330	71	10	the	the	DET
ajst-22330	71	11	local	local	ADJ
ajst-22330	71	12	extremum	extremum	NOUN
ajst-22330	71	13	in	in	ADP
ajst-22330	71	14	the	the	DET
ajst-22330	71	15	loss	loss	NOUN
ajst-22330	71	16	landscape	landscape	NOUN
ajst-22330	71	17	in	in	ADP
ajst-22330	71	18	which	which	PRON
ajst-22330	71	19	a	a	DET
ajst-22330	71	20	large	large	ADJ
ajst-22330	71	21	proportion	proportion	NOUN
ajst-22330	71	22	of	of	ADP
ajst-22330	71	23	eigenvalues	eigenvalue	NOUN
ajst-22330	71	24	in	in	ADP
ajst-22330	71	25	the	the	DET
ajst-22330	71	26	hessian	hessian	ADJ
ajst-22330	71	27	matrix	matrix	NOUN
ajst-22330	71	28	are	be	AUX
ajst-22330	71	29	0	0	NUM
ajst-22330	71	30	and	and	CCONJ
ajst-22330	71	31	only	only	ADV
ajst-22330	71	32	a	a	DET
ajst-22330	71	33	very	very	ADV
ajst-22330	71	34	small	small	ADJ
ajst-22330	71	35	number	number	NOUN
ajst-22330	71	36	of	of	ADP
ajst-22330	71	37	positive	positive	ADJ
ajst-22330	71	38	and	and	CCONJ
ajst-22330	71	39	negative	negative	ADJ
ajst-22330	71	40	eigenvalues	eigenvalue	NOUN
ajst-22330	71	41	.	.	PUNCT
ajst-22330	72	1	in	in	ADP
ajst-22330	72	2	this	this	DET
ajst-22330	72	3	way	way	NOUN
ajst-22330	72	4	,	,	PUNCT
ajst-22330	72	5	an	an	DET
ajst-22330	72	6	objective	objective	ADJ
ajst-22330	72	7	function	function	NOUN
ajst-22330	72	8	based	base	VERB
ajst-22330	72	9	on	on	ADP
ajst-22330	72	10	local	local	ADJ
ajst-22330	72	11	entropy	entropy	NOUN
ajst-22330	72	12	is	be	AUX
ajst-22330	72	13	constructed	construct	VERB
ajst-22330	72	14	,	,	PUNCT
ajst-22330	72	15	which	which	PRON
ajst-22330	72	16	can	can	AUX
ajst-22330	72	17	find	find	VERB
ajst-22330	72	18	the	the	DET
ajst-22330	72	19	extreme	extreme	ADJ
ajst-22330	72	20	value	value	NOUN
ajst-22330	72	21	with	with	ADP
ajst-22330	72	22	good	good	ADJ
ajst-22330	72	23	generalization	generalization	NOUN
ajst-22330	72	24	ability	ability	NOUN
ajst-22330	72	25	in	in	ADP
ajst-22330	72	26	the	the	DET
ajst-22330	72	27	flat	flat	ADJ
ajst-22330	72	28	area	area	NOUN
ajst-22330	72	29	of	of	ADP
ajst-22330	72	30	the	the	DET
ajst-22330	72	31	loss	loss	NOUN
ajst-22330	72	32	landscape	landscape	NOUN
ajst-22330	72	33	,	,	PUNCT
ajst-22330	72	34	and	and	CCONJ
ajst-22330	72	35	avoid	avoid	VERB
ajst-22330	72	36	the	the	DET
ajst-22330	72	37	extreme	extreme	ADJ
ajst-22330	72	38	value	value	NOUN
ajst-22330	72	39	with	with	ADP
ajst-22330	72	40	poor	poor	ADJ
ajst-22330	72	41	generalization	generalization	NOUN
ajst-22330	72	42	ability	ability	NOUN
ajst-22330	72	43	located	locate	VERB
ajst-22330	72	44	in	in	ADP
ajst-22330	72	45	the	the	DET
ajst-22330	72	46	sharp	sharp	ADJ
ajst-22330	72	47	valley	valley	NOUN
ajst-22330	72	48	.	.	PUNCT
ajst-22330	73	1	izmailov	izmailov	PROPN
ajst-22330	73	2	et	et	PROPN
ajst-22330	73	3	al.[24	al.[24	PROPN
ajst-22330	73	4	]	]	PUNCT
ajst-22330	73	5	proposed	propose	VERB
ajst-22330	73	6	simple	simple	ADJ
ajst-22330	73	7	averaging	averaging	NOUN
ajst-22330	73	8	of	of	ADP
ajst-22330	73	9	multiple	multiple	ADJ
ajst-22330	73	10	points	point	NOUN
ajst-22330	73	11	along	along	ADP
ajst-22330	73	12	the	the	DET
ajst-22330	73	13	sgd	sgd	PROPN
ajst-22330	73	14	trajectory	trajectory	NOUN
ajst-22330	73	15	,	,	PUNCT
ajst-22330	73	16	which	which	PRON
ajst-22330	73	17	can	can	AUX
ajst-22330	73	18	find	find	VERB
ajst-22330	73	19	a	a	DET
ajst-22330	73	20	flatter	flatter	ADJ
ajst-22330	73	21	optimal	optimal	ADJ
ajst-22330	73	22	value	value	NOUN
ajst-22330	73	23	than	than	SCONJ
ajst-22330	73	24	sgd	sgd	VERB
ajst-22330	73	25	with	with	ADP
ajst-22330	73	26	almost	almost	ADV
ajst-22330	73	27	no	no	PRON
ajst-22330	73	28	additional	additional	ADJ
ajst-22330	73	29	computational	computational	ADJ
ajst-22330	73	30	overhead	overhead	NOUN
ajst-22330	73	31	while	while	SCONJ
ajst-22330	73	32	improving	improve	VERB
ajst-22330	73	33	the	the	DET
ajst-22330	73	34	generalization	generalization	NOUN
ajst-22330	73	35	ability	ability	NOUN
ajst-22330	73	36	.	.	PUNCT
ajst-22330	74	1	and	and	CCONJ
ajst-22330	74	2	the	the	DET
ajst-22330	74	3	sharpness	sharpness	NOUN
ajst-22330	74	4	-	-	PUNCT
ajst-22330	74	5	aware	aware	ADJ
ajst-22330	74	6	minimization	minimization	NOUN
ajst-22330	74	7	algorithm	algorithm	NOUN
ajst-22330	74	8	proposed	propose	VERB
ajst-22330	74	9	by	by	ADP
ajst-22330	74	10	foret	foret	PROPN
ajst-22330	74	11	et	et	PROPN
ajst-22330	74	12	al.[25	al.[25	PROPN
ajst-22330	74	13	]	]	PUNCT
ajst-22330	74	14	proposes	propose	VERB
ajst-22330	74	15	to	to	PART
ajst-22330	74	16	find	find	VERB
ajst-22330	74	17	the	the	DET
ajst-22330	74	18	flat	flat	ADJ
ajst-22330	74	19	optimal	optimal	ADJ
ajst-22330	74	20	value	value	NOUN
ajst-22330	74	21	by	by	ADP
ajst-22330	74	22	calculating	calculate	VERB
ajst-22330	74	23	the	the	DET
ajst-22330	74	24	sharpness	sharpness	NOUN
ajst-22330	74	25	in	in	ADP
ajst-22330	74	26	terms	term	NOUN
ajst-22330	74	27	of	of	ADP
ajst-22330	74	28	loss	loss	NOUN
ajst-22330	74	29	landscape	landscape	NOUN
ajst-22330	74	30	.	.	PUNCT
ajst-22330	75	1	we	we	PRON
ajst-22330	75	2	present	present	VERB
ajst-22330	75	3	a	a	DET
ajst-22330	75	4	diagram	diagram	NOUN
ajst-22330	75	5	of	of	ADP
ajst-22330	75	6	machine	machine	NOUN
ajst-22330	75	7	learning	learning	NOUN
ajst-22330	75	8	,	,	PUNCT
ajst-22330	75	9	federated	federated	ADJ
ajst-22330	75	10	learning	learning	NOUN
ajst-22330	75	11	,	,	PUNCT
ajst-22330	75	12	meta	meta	PROPN
ajst-22330	75	13	-	-	PUNCT
ajst-22330	75	14	learning	learning	NOUN
ajst-22330	75	15	,	,	PUNCT
ajst-22330	75	16	and	and	CCONJ
ajst-22330	75	17	federated	federated	ADJ
ajst-22330	75	18	metalearning	metalearning	NOUN
ajst-22330	75	19	in	in	ADP
ajst-22330	75	20	figure	figure	NOUN
ajst-22330	75	21	3	3	NUM
ajst-22330	75	22	.	.	PUNCT
ajst-22330	75	23	figure	figure	NOUN
ajst-22330	75	24	3	3	NUM
ajst-22330	75	25	.	.	PUNCT
ajst-22330	75	26	logical	logical	ADJ
ajst-22330	75	27	graph	graph	NOUN
ajst-22330	75	28	5	5	NUM
ajst-22330	75	29	.	.	PUNCT
ajst-22330	75	30	summary	summary	NOUN
ajst-22330	75	31	federated	federate	VERB
ajst-22330	75	32	meta	meta	ADV
ajst-22330	75	33	-	-	PUNCT
ajst-22330	75	34	learning	learning	NOUN
ajst-22330	75	35	is	be	AUX
ajst-22330	75	36	an	an	DET
ajst-22330	75	37	optimization	optimization	NOUN
ajst-22330	75	38	algorithm	algorithm	NOUN
ajst-22330	75	39	which	which	PRON
ajst-22330	75	40	aims	aim	VERB
ajst-22330	75	41	to	to	PART
ajst-22330	75	42	solve	solve	VERB
ajst-22330	75	43	the	the	DET
ajst-22330	75	44	problems	problem	NOUN
ajst-22330	75	45	existing	exist	VERB
ajst-22330	75	46	in	in	ADP
ajst-22330	75	47	the	the	DET
ajst-22330	75	48	actual	actual	ADJ
ajst-22330	75	49	production	production	NOUN
ajst-22330	75	50	.	.	PUNCT
ajst-22330	76	1	federated	federate	VERB
ajst-22330	76	2	meta	meta	ADV
ajst-22330	76	3	-	-	PUNCT
ajst-22330	76	4	learning	learning	NOUN
ajst-22330	76	5	not	not	PART
ajst-22330	76	6	only	only	ADV
ajst-22330	76	7	solves	solve	VERB
ajst-22330	76	8	the	the	DET
ajst-22330	76	9	problem	problem	NOUN
ajst-22330	76	10	of	of	ADP
ajst-22330	76	11	data	data	NOUN
ajst-22330	76	12	islands	island	NOUN
ajst-22330	76	13	,	,	PUNCT
ajst-22330	76	14	but	but	CCONJ
ajst-22330	76	15	also	also	ADV
ajst-22330	76	16	can	can	AUX
ajst-22330	76	17	use	use	VERB
ajst-22330	76	18	the	the	DET
ajst-22330	76	19	fast	fast	ADJ
ajst-22330	76	20	learning	learning	NOUN
ajst-22330	76	21	ability	ability	NOUN
ajst-22330	76	22	of	of	ADP
ajst-22330	76	23	meta	meta	ADV
ajst-22330	76	24	-	-	PUNCT
ajst-22330	76	25	learning	learning	NOUN
ajst-22330	76	26	to	to	PART
ajst-22330	76	27	provide	provide	VERB
ajst-22330	76	28	different	different	ADJ
ajst-22330	76	29	models	model	NOUN
ajst-22330	76	30	for	for	ADP
ajst-22330	76	31	different	different	ADJ
ajst-22330	76	32	users	user	NOUN
ajst-22330	76	33	with	with	ADP
ajst-22330	76	34	a	a	DET
ajst-22330	76	35	small	small	ADJ
ajst-22330	76	36	amount	amount	NOUN
ajst-22330	76	37	of	of	ADP
ajst-22330	76	38	data	datum	NOUN
ajst-22330	76	39	.	.	PUNCT
ajst-22330	77	1	despite	despite	SCONJ
ajst-22330	77	2	the	the	DET
ajst-22330	77	3	success	success	NOUN
ajst-22330	77	4	of	of	ADP
ajst-22330	77	5	federated	federated	ADJ
ajst-22330	77	6	meta	meta	NOUN
ajst-22330	77	7	-	-	PUNCT
ajst-22330	77	8	learning	learning	NOUN
ajst-22330	77	9	,	,	PUNCT
ajst-22330	77	10	it	it	PRON
ajst-22330	77	11	still	still	ADV
ajst-22330	77	12	has	have	VERB
ajst-22330	77	13	many	many	ADJ
ajst-22330	77	14	shortcomings	shortcoming	NOUN
ajst-22330	77	15	,	,	PUNCT
ajst-22330	77	16	such	such	ADJ
ajst-22330	77	17	as	as	ADP
ajst-22330	77	18	limited	limited	ADJ
ajst-22330	77	19	generalization	generalization	NOUN
ajst-22330	77	20	ability	ability	NOUN
ajst-22330	77	21	,	,	PUNCT
ajst-22330	77	22	29	29	NUM
ajst-22330	77	23	communication	communication	NOUN
ajst-22330	77	24	bottleneck	bottleneck	NOUN
ajst-22330	77	25	,	,	PUNCT
ajst-22330	77	26	vulnerability	vulnerability	NOUN
ajst-22330	77	27	to	to	ADP
ajst-22330	77	28	adversarial	adversarial	ADJ
ajst-22330	77	29	attacks	attack	NOUN
ajst-22330	77	30	,	,	PUNCT
ajst-22330	77	31	distribution	distribution	NOUN
ajst-22330	77	32	shift	shift	NOUN
ajst-22330	77	33	and	and	CCONJ
ajst-22330	77	34	so	so	ADV
ajst-22330	77	35	on	on	ADV
ajst-22330	77	36	.	.	PUNCT
ajst-22330	78	1	this	this	PRON
ajst-22330	78	2	points	point	VERB
ajst-22330	78	3	out	out	ADP
ajst-22330	78	4	a	a	DET
ajst-22330	78	5	certain	certain	ADJ
ajst-22330	78	6	direction	direction	NOUN
ajst-22330	78	7	for	for	ADP
ajst-22330	78	8	the	the	DET
ajst-22330	78	9	subsequent	subsequent	ADJ
ajst-22330	78	10	research	research	NOUN
ajst-22330	78	11	on	on	ADP
ajst-22330	78	12	federated	federated	ADJ
ajst-22330	78	13	metalearning	metalearning	NOUN
ajst-22330	78	14	.	.	PUNCT
ajst-22330	79	1	acknowledgments	acknowledgment	NOUN
ajst-22330	79	2	this	this	DET
ajst-22330	79	3	work	work	NOUN
ajst-22330	79	4	was	be	AUX
ajst-22330	79	5	supported	support	VERB
ajst-22330	79	6	in	in	ADP
ajst-22330	79	7	part	part	NOUN
ajst-22330	79	8	by	by	ADP
ajst-22330	79	9	the	the	DET
ajst-22330	79	10	key	key	ADJ
ajst-22330	79	11	technologies	technology	NOUN
ajst-22330	79	12	r	r	PROPN
ajst-22330	79	13	&	&	CCONJ
ajst-22330	79	14	d	d	PROPN
ajst-22330	79	15	program	program	NOUN
ajst-22330	79	16	of	of	ADP
ajst-22330	79	17	henan	henan	PROPN
ajst-22330	79	18	province	province	PROPN
ajst-22330	79	19	under	under	ADP
ajst-22330	79	20	grant	grant	PROPN
ajst-22330	79	21	no	no	NOUN
ajst-22330	79	22	.	.	NOUN
ajst-22330	79	23	242102	242102	NUM
ajst-22330	79	24	210102	210102	NUM
ajst-22330	79	25	and	and	CCONJ
ajst-22330	79	26	222102210080	222102210080	NUM
ajst-22330	79	27	,	,	PUNCT
ajst-22330	79	28	in	in	ADP
ajst-22330	79	29	part	part	NOUN
ajst-22330	79	30	by	by	ADP
ajst-22330	79	31	the	the	DET
ajst-22330	79	32	joint	joint	ADJ
ajst-22330	79	33	funds	fund	NOUN
ajst-22330	79	34	for	for	ADP
ajst-22330	79	35	science	science	NOUN
ajst-22330	79	36	and	and	CCONJ
ajst-22330	79	37	technology	technology	NOUN
ajst-22330	79	38	research	research	NOUN
ajst-22330	79	39	and	and	CCONJ
ajst-22330	79	40	development	development	NOUN
ajst-22330	79	41	plan	plan	NOUN
ajst-22330	79	42	of	of	ADP
ajst-22330	79	43	henan	henan	PROPN
ajst-22330	79	44	province	province	PROPN
ajst-22330	79	45	under	under	ADP
ajst-22330	79	46	grant	grant	PROPN
ajst-22330	79	47	no	no	NOUN
ajst-22330	79	48	.	.	NOUN
ajst-22330	79	49	222103810031	222103810031	NUM
ajst-22330	79	50	.	.	PUNCT
ajst-22330	80	1	references	reference	NOUN
ajst-22330	80	2	[	[	X
ajst-22330	80	3	1	1	NUM
ajst-22330	80	4	]	]	X
ajst-22330	80	5	mjolsness	mjolsness	ADJ
ajst-22330	80	6	e	e	NOUN
ajst-22330	80	7	,	,	PUNCT
ajst-22330	80	8	decoste	decoste	VERB
ajst-22330	80	9	d.	d.	PROPN
ajst-22330	80	10	machine	machine	NOUN
ajst-22330	80	11	learning	learn	VERB
ajst-22330	80	12	for	for	ADP
ajst-22330	80	13	science	science	NOUN
ajst-22330	80	14	:	:	PUNCT
ajst-22330	80	15	state	state	NOUN
ajst-22330	80	16	of	of	ADP
ajst-22330	80	17	the	the	DET
ajst-22330	80	18	art	art	NOUN
ajst-22330	80	19	and	and	CCONJ
ajst-22330	80	20	future	future	ADJ
ajst-22330	80	21	prospects	prospect	NOUN
ajst-22330	80	22	[	[	X
ajst-22330	80	23	j	j	X
ajst-22330	80	24	]	]	X
ajst-22330	80	25	.	.	PUNCT
ajst-22330	81	1	science	science	NOUN
ajst-22330	81	2	,	,	PUNCT
ajst-22330	81	3	2001	2001	NUM
ajst-22330	81	4	,	,	PUNCT
ajst-22330	81	5	293(5537	293(5537	NUM
ajst-22330	81	6	):	):	PUNCT
ajst-22330	81	7	2051	2051	NUM
ajst-22330	81	8	-	-	SYM
ajst-22330	81	9	2055	2055	NUM
ajst-22330	81	10	.	.	PUNCT
ajst-22330	82	1	[	[	X
ajst-22330	82	2	2	2	X
ajst-22330	82	3	]	]	X
ajst-22330	82	4	silver	silver	NOUN
ajst-22330	82	5	d	d	PROPN
ajst-22330	82	6	,	,	PUNCT
ajst-22330	82	7	huang	huang	PROPN
ajst-22330	82	8	a	a	PROPN
ajst-22330	82	9	,	,	PUNCT
ajst-22330	82	10	maddison	maddison	PROPN
ajst-22330	82	11	c	c	PROPN
ajst-22330	82	12	j	j	PROPN
ajst-22330	82	13	,	,	PUNCT
ajst-22330	82	14	et	et	PROPN
ajst-22330	82	15	al	al	PROPN
ajst-22330	82	16	.	.	PUNCT
ajst-22330	82	17	mastering	master	VERB
ajst-22330	82	18	the	the	DET
ajst-22330	82	19	game	game	NOUN
ajst-22330	82	20	of	of	ADP
ajst-22330	82	21	go	go	NOUN
ajst-22330	82	22	with	with	ADP
ajst-22330	82	23	deep	deep	ADJ
ajst-22330	82	24	neural	neural	ADJ
ajst-22330	82	25	networks	network	NOUN
ajst-22330	82	26	and	and	CCONJ
ajst-22330	82	27	tree	tree	NOUN
ajst-22330	82	28	search[j	search[j	PROPN
ajst-22330	82	29	]	]	PUNCT
ajst-22330	82	30	.	.	PUNCT
ajst-22330	83	1	nature	nature	NOUN
ajst-22330	83	2	,	,	PUNCT
ajst-22330	83	3	2016	2016	NUM
ajst-22330	83	4	,	,	PUNCT
ajst-22330	83	5	529(7587	529(7587	NUM
ajst-22330	83	6	):	):	PUNCT
ajst-22330	83	7	484	484	NUM
ajst-22330	83	8	-	-	SYM
ajst-22330	83	9	489	489	NUM
ajst-22330	83	10	.	.	PUNCT
ajst-22330	84	1	[	[	X
ajst-22330	84	2	3	3	X
ajst-22330	84	3	]	]	X
ajst-22330	84	4	moraveik	moraveik	PROPN
ajst-22330	84	5	m	m	PROPN
ajst-22330	84	6	,	,	PUNCT
ajst-22330	84	7	schmid	schmid	PROPN
ajst-22330	84	8	m	m	PROPN
ajst-22330	84	9	,	,	PUNCT
ajst-22330	84	10	burch	burch	PROPN
ajst-22330	84	11	n	n	CCONJ
ajst-22330	84	12	,	,	PUNCT
ajst-22330	84	13	et	et	PROPN
ajst-22330	84	14	al	al	PROPN
ajst-22330	84	15	.	.	PROPN
ajst-22330	84	16	deepstack	deepstack	PROPN
ajst-22330	84	17	:	:	PUNCT
ajst-22330	84	18	expertlevel	expertlevel	VERB
ajst-22330	84	19	artificial	artificial	ADJ
ajst-22330	84	20	intelligence	intelligence	NOUN
ajst-22330	84	21	in	in	ADP
ajst-22330	84	22	heads	head	NOUN
ajst-22330	84	23	-	-	PUNCT
ajst-22330	84	24	up	up	ADP
ajst-22330	84	25	no	no	DET
ajst-22330	84	26	-	-	PUNCT
ajst-22330	84	27	limit	limit	NOUN
ajst-22330	84	28	poker[j	poker[j	NOUN
ajst-22330	84	29	]	]	PUNCT
ajst-22330	84	30	.	.	PUNCT
ajst-22330	85	1	science	science	NOUN
ajst-22330	85	2	,	,	PUNCT
ajst-22330	85	3	2017	2017	NUM
ajst-22330	85	4	,	,	PUNCT
ajst-22330	85	5	356(6337	356(6337	NUM
ajst-22330	85	6	):	):	PUNCT
ajst-22330	85	7	508	508	NUM
ajst-22330	85	8	-	-	SYM
ajst-22330	85	9	513	513	NUM
ajst-22330	85	10	.	.	PUNCT
ajst-22330	86	1	[	[	X
ajst-22330	86	2	4	4	NUM
ajst-22330	86	3	]	]	X
ajst-22330	86	4	devlin	devlin	PROPN
ajst-22330	86	5	j	j	PROPN
ajst-22330	86	6	,	,	PUNCT
ajst-22330	86	7	chang	chang	PROPN
ajst-22330	86	8	m	m	PROPN
ajst-22330	86	9	w	w	PROPN
ajst-22330	86	10	,	,	PUNCT
ajst-22330	86	11	lee	lee	PROPN
ajst-22330	86	12	k	k	PROPN
ajst-22330	86	13	,	,	PUNCT
ajst-22330	86	14	et	et	PROPN
ajst-22330	86	15	al	al	PROPN
ajst-22330	86	16	.	.	PUNCT
ajst-22330	86	17	bert	bert	PROPN
ajst-22330	86	18	:	:	PUNCT
ajst-22330	86	19	pre	pre	ADJ
ajst-22330	86	20	-	-	NOUN
ajst-22330	86	21	training	training	NOUN
ajst-22330	86	22	of	of	ADP
ajst-22330	86	23	deep	deep	ADJ
ajst-22330	86	24	bidirectional	bidirectional	ADJ
ajst-22330	86	25	transformers	transformer	NOUN
ajst-22330	86	26	for	for	ADP
ajst-22330	86	27	language	language	NOUN
ajst-22330	86	28	understanding[j	understanding[j	NOUN
ajst-22330	86	29	]	]	PUNCT
ajst-22330	86	30	.	.	PUNCT
ajst-22330	87	1	arxiv	arxiv	PROPN
ajst-22330	87	2	preprint	preprint	PROPN
ajst-22330	87	3	arxiv:1810.04805	arxiv:1810.04805	PROPN
ajst-22330	87	4	,	,	PUNCT
ajst-22330	87	5	2018	2018	NUM
ajst-22330	87	6	.	.	PUNCT
ajst-22330	88	1	[	[	X
ajst-22330	88	2	5	5	X
ajst-22330	88	3	]	]	X
ajst-22330	88	4	sun	sun	NOUN
ajst-22330	88	5	p	p	NOUN
ajst-22330	88	6	,	,	PUNCT
ajst-22330	88	7	kretzschmar	kretzschmar	PROPN
ajst-22330	88	8	h	h	PROPN
ajst-22330	88	9	,	,	PUNCT
ajst-22330	88	10	dotiwalla	dotiwalla	NOUN
ajst-22330	88	11	x	x	NOUN
ajst-22330	88	12	,	,	PUNCT
ajst-22330	88	13	et	et	PROPN
ajst-22330	88	14	al	al	PROPN
ajst-22330	88	15	.	.	PUNCT
ajst-22330	88	16	scalability	scalability	NOUN
ajst-22330	88	17	in	in	ADP
ajst-22330	88	18	perception	perception	NOUN
ajst-22330	88	19	for	for	ADP
ajst-22330	88	20	autonomous	autonomous	ADJ
ajst-22330	88	21	driving	driving	NOUN
ajst-22330	88	22	:	:	PUNCT
ajst-22330	88	23	waymo	waymo	NOUN
ajst-22330	88	24	open	open	ADJ
ajst-22330	88	25	dataset[c	dataset[c	NOUN
ajst-22330	88	26	]	]	PUNCT
ajst-22330	88	27	.	.	PUNCT
ajst-22330	89	1	proceedings	proceeding	NOUN
ajst-22330	89	2	of	of	ADP
ajst-22330	89	3	the	the	DET
ajst-22330	89	4	ieee	ieee	NOUN
ajst-22330	89	5	/	/	SYM
ajst-22330	89	6	cvf	cvf	NOUN
ajst-22330	89	7	conference	conference	NOUN
ajst-22330	89	8	on	on	ADP
ajst-22330	89	9	computer	computer	NOUN
ajst-22330	89	10	vision	vision	NOUN
ajst-22330	89	11	and	and	CCONJ
ajst-22330	89	12	pattern	pattern	NOUN
ajst-22330	89	13	recognition	recognition	NOUN
ajst-22330	89	14	.	.	PUNCT
ajst-22330	90	1	2020	2020	NUM
ajst-22330	90	2	:	:	PUNCT
ajst-22330	90	3	2446	2446	NUM
ajst-22330	90	4	-	-	SYM
ajst-22330	90	5	2454	2454	NUM
ajst-22330	90	6	.	.	PUNCT
ajst-22330	91	1	[	[	X
ajst-22330	91	2	6	6	NUM
ajst-22330	91	3	]	]	PUNCT
ajst-22330	91	4	konečný	konečný	PROPN
ajst-22330	91	5	j	j	PROPN
ajst-22330	91	6	,	,	PUNCT
ajst-22330	91	7	mcmahan	mcmahan	PROPN
ajst-22330	91	8	h	h	PROPN
ajst-22330	91	9	b	b	PROPN
ajst-22330	91	10	,	,	PUNCT
ajst-22330	91	11	ramage	ramage	NOUN
ajst-22330	91	12	d	d	PROPN
ajst-22330	91	13	,	,	PUNCT
ajst-22330	91	14	et	et	PROPN
ajst-22330	91	15	al	al	PROPN
ajst-22330	91	16	.	.	PROPN
ajst-22330	91	17	federated	federated	ADJ
ajst-22330	91	18	optimization	optimization	NOUN
ajst-22330	91	19	:	:	PUNCT
ajst-22330	91	20	distributed	distribute	VERB
ajst-22330	91	21	machine	machine	NOUN
ajst-22330	91	22	learning	learn	VERB
ajst-22330	91	23	for	for	ADP
ajst-22330	91	24	on	on	ADP
ajst-22330	91	25	-	-	PUNCT
ajst-22330	91	26	device	device	NOUN
ajst-22330	91	27	intelligence[j	intelligence[j	NOUN
ajst-22330	91	28	]	]	PUNCT
ajst-22330	91	29	.	.	PUNCT
ajst-22330	92	1	arxiv	arxiv	PROPN
ajst-22330	92	2	preprint	preprint	VERB
ajst-22330	92	3	arxiv:1610.02527	arxiv:1610.02527	PROPN
ajst-22330	92	4	,	,	PUNCT
ajst-22330	92	5	2016	2016	NUM
ajst-22330	92	6	.	.	PUNCT
ajst-22330	93	1	[	[	X
ajst-22330	93	2	7	7	X
ajst-22330	93	3	]	]	X
ajst-22330	93	4	wang	wang	PROPN
ajst-22330	93	5	j	j	PROPN
ajst-22330	93	6	,	,	PUNCT
ajst-22330	93	7	tantia	tantia	PROPN
ajst-22330	93	8	v	v	NOUN
ajst-22330	93	9	,	,	PUNCT
ajst-22330	93	10	ballas	ballas	PROPN
ajst-22330	93	11	n	n	CCONJ
ajst-22330	93	12	,	,	PUNCT
ajst-22330	93	13	et	et	PROPN
ajst-22330	93	14	al	al	PROPN
ajst-22330	93	15	.	.	PROPN
ajst-22330	93	16	slowmo	slowmo	ADJ
ajst-22330	93	17	:	:	PUNCT
ajst-22330	93	18	improving	improve	VERB
ajst-22330	93	19	communication	communication	NOUN
ajst-22330	93	20	-	-	PUNCT
ajst-22330	93	21	efficient	efficient	ADJ
ajst-22330	93	22	distributed	distribute	VERB
ajst-22330	93	23	sgd	sgd	NOUN
ajst-22330	93	24	with	with	ADP
ajst-22330	93	25	slow	slow	ADJ
ajst-22330	93	26	momentum	momentum	NOUN
ajst-22330	94	1	[	[	X
ajst-22330	94	2	j	j	X
ajst-22330	94	3	]	]	X
ajst-22330	94	4	.	.	PUNCT
ajst-22330	95	1	arxiv	arxiv	PROPN
ajst-22330	95	2	preprint	preprint	PROPN
ajst-22330	95	3	arxiv:1910.00643	arxiv:1910.00643	NOUN
ajst-22330	95	4	,	,	PUNCT
ajst-22330	95	5	2019	2019	NUM
ajst-22330	95	6	.	.	PUNCT
ajst-22330	96	1	[	[	X
ajst-22330	96	2	8	8	NUM
ajst-22330	96	3	]	]	PUNCT
ajst-22330	96	4	khanduri	khanduri	PROPN
ajst-22330	96	5	p	p	PROPN
ajst-22330	96	6	,	,	PUNCT
ajst-22330	96	7	sharma	sharma	PROPN
ajst-22330	96	8	p	p	PROPN
ajst-22330	96	9	,	,	PUNCT
ajst-22330	96	10	yang	yang	PROPN
ajst-22330	96	11	h	h	PROPN
ajst-22330	96	12	,	,	PUNCT
ajst-22330	96	13	et	et	PROPN
ajst-22330	96	14	al	al	PROPN
ajst-22330	96	15	.	.	PROPN
ajst-22330	96	16	stem	stem	PROPN
ajst-22330	96	17	:	:	PUNCT
ajst-22330	96	18	a	a	DET
ajst-22330	96	19	stochastic	stochastic	ADJ
ajst-22330	96	20	twosided	twoside	VERB
ajst-22330	96	21	momentum	momentum	NOUN
ajst-22330	96	22	algorithm	algorithm	NOUN
ajst-22330	96	23	achieving	achieve	VERB
ajst-22330	96	24	near	near	ADP
ajst-22330	96	25	-	-	PUNCT
ajst-22330	96	26	optimal	optimal	ADJ
ajst-22330	96	27	sample	sample	NOUN
ajst-22330	96	28	and	and	CCONJ
ajst-22330	96	29	communication	communication	NOUN
ajst-22330	96	30	complexities	complexity	NOUN
ajst-22330	96	31	for	for	ADP
ajst-22330	96	32	federated	federated	ADJ
ajst-22330	96	33	learning[j	learning[j	NOUN
ajst-22330	96	34	]	]	PUNCT
ajst-22330	96	35	.	.	PUNCT
ajst-22330	97	1	advances	advance	NOUN
ajst-22330	97	2	in	in	ADP
ajst-22330	97	3	neural	neural	ADJ
ajst-22330	97	4	information	information	NOUN
ajst-22330	97	5	processing	processing	NOUN
ajst-22330	97	6	systems	system	NOUN
ajst-22330	97	7	,	,	PUNCT
ajst-22330	97	8	2021	2021	NUM
ajst-22330	97	9	,	,	PUNCT
ajst-22330	97	10	34	34	NUM
ajst-22330	97	11	:	:	SYM
ajst-22330	97	12	6050	6050	NUM
ajst-22330	97	13	-	-	SYM
ajst-22330	97	14	6061	6061	NUM
ajst-22330	97	15	.	.	PUNCT
ajst-22330	98	1	[	[	X
ajst-22330	98	2	9	9	NUM
ajst-22330	98	3	]	]	X
ajst-22330	98	4	gupta	gupta	PROPN
ajst-22330	98	5	s	s	PROPN
ajst-22330	98	6	,	,	PUNCT
ajst-22330	98	7	ahuja	ahuja	PROPN
ajst-22330	98	8	k	k	PROPN
ajst-22330	98	9	,	,	PUNCT
ajst-22330	98	10	havaei	havaei	PROPN
ajst-22330	98	11	m	m	PROPN
ajst-22330	98	12	,	,	PUNCT
ajst-22330	98	13	et	et	PROPN
ajst-22330	98	14	al	al	PROPN
ajst-22330	98	15	.	.	PROPN
ajst-22330	99	1	fl	fl	PROPN
ajst-22330	99	2	games	games	PROPN
ajst-22330	99	3	:	:	PUNCT
ajst-22330	99	4	a	a	DET
ajst-22330	99	5	federated	federated	ADJ
ajst-22330	99	6	learning	learning	NOUN
ajst-22330	99	7	framework	framework	NOUN
ajst-22330	99	8	for	for	ADP
ajst-22330	99	9	distribution	distribution	NOUN
ajst-22330	99	10	shifts[j	shifts[j	PROPN
ajst-22330	99	11	]	]	PUNCT
ajst-22330	99	12	.	.	PUNCT
ajst-22330	100	1	arxiv	arxiv	PROPN
ajst-22330	100	2	preprint	preprint	PROPN
ajst-22330	100	3	arxiv:2205.11101	arxiv:2205.11101	PROPN
ajst-22330	100	4	,	,	PUNCT
ajst-22330	100	5	2022	2022	NUM
ajst-22330	100	6	.	.	PUNCT
ajst-22330	101	1	[	[	X
ajst-22330	101	2	10	10	NUM
ajst-22330	101	3	]	]	X
ajst-22330	101	4	yoon	yoon	PROPN
ajst-22330	101	5	t	t	PROPN
ajst-22330	101	6	,	,	PUNCT
ajst-22330	101	7	shin	shin	PROPN
ajst-22330	101	8	s	s	PROPN
ajst-22330	101	9	,	,	PUNCT
ajst-22330	101	10	hwang	hwang	PROPN
ajst-22330	101	11	s	s	PROPN
ajst-22330	101	12	j	j	PROPN
ajst-22330	101	13	,	,	PUNCT
ajst-22330	101	14	et	et	PROPN
ajst-22330	101	15	al	al	PROPN
ajst-22330	101	16	.	.	PROPN
ajst-22330	101	17	fedmix	fedmix	PROPN
ajst-22330	101	18	:	:	PUNCT
ajst-22330	101	19	approximation	approximation	NOUN
ajst-22330	101	20	of	of	ADP
ajst-22330	101	21	mixup	mixup	NOUN
ajst-22330	101	22	under	under	ADP
ajst-22330	101	23	mean	mean	PROPN
ajst-22330	101	24	augmented	augment	VERB
ajst-22330	101	25	federated	federated	ADJ
ajst-22330	101	26	learning[j	learning[j	NOUN
ajst-22330	101	27	]	]	PUNCT
ajst-22330	101	28	.	.	PUNCT
ajst-22330	102	1	arxiv	arxiv	PROPN
ajst-22330	102	2	preprint	preprint	NOUN
ajst-22330	102	3	arxiv:2107.00233	arxiv:2107.00233	NOUN
ajst-22330	102	4	,	,	PUNCT
ajst-22330	102	5	2021	2021	NUM
ajst-22330	102	6	.	.	PUNCT
ajst-22330	103	1	[	[	X
ajst-22330	103	2	11	11	NUM
ajst-22330	103	3	]	]	PUNCT
ajst-22330	103	4	thrun	thrun	NOUN
ajst-22330	103	5	s	s	PROPN
ajst-22330	103	6	,	,	PUNCT
ajst-22330	103	7	pratt	pratt	PROPN
ajst-22330	103	8	l.	l.	PROPN
ajst-22330	103	9	learning	learning	PROPN
ajst-22330	103	10	to	to	PART
ajst-22330	103	11	learn	learn	VERB
ajst-22330	103	12	:	:	PUNCT
ajst-22330	103	13	introduction	introduction	NOUN
ajst-22330	103	14	and	and	CCONJ
ajst-22330	103	15	overview[m	overview[m	NOUN
ajst-22330	103	16	]	]	PUNCT
ajst-22330	103	17	.	.	PUNCT
ajst-22330	104	1	learning	learn	VERB
ajst-22330	104	2	to	to	PART
ajst-22330	104	3	learn	learn	VERB
ajst-22330	104	4	.	.	PUNCT
ajst-22330	105	1	boston	boston	PROPN
ajst-22330	105	2	,	,	PUNCT
ajst-22330	105	3	ma	ma	PROPN
ajst-22330	105	4	:	:	PUNCT
ajst-22330	105	5	springer	springer	NOUN
ajst-22330	105	6	us	we	PRON
ajst-22330	105	7	,	,	PUNCT
ajst-22330	105	8	1998	1998	NUM
ajst-22330	105	9	:	:	PUNCT
ajst-22330	105	10	3	3	NUM
ajst-22330	105	11	-	-	SYM
ajst-22330	105	12	17	17	NUM
ajst-22330	105	13	.	.	PUNCT
ajst-22330	106	1	[	[	X
ajst-22330	106	2	12	12	NUM
ajst-22330	106	3	]	]	PUNCT
ajst-22330	106	4	metz	metz	PROPN
ajst-22330	106	5	l	l	PROPN
ajst-22330	106	6	,	,	PUNCT
ajst-22330	106	7	maheswaranathan	maheswaranathan	ADJ
ajst-22330	106	8	n	n	CCONJ
ajst-22330	106	9	,	,	PUNCT
ajst-22330	106	10	cheung	cheung	PROPN
ajst-22330	106	11	b	b	PROPN
ajst-22330	106	12	,	,	PUNCT
ajst-22330	106	13	et	et	PROPN
ajst-22330	106	14	al	al	PROPN
ajst-22330	106	15	.	.	PUNCT
ajst-22330	106	16	meta	meta	ADJ
ajst-22330	106	17	-	-	PUNCT
ajst-22330	106	18	learning	learn	VERB
ajst-22330	106	19	update	update	NOUN
ajst-22330	106	20	rules	rule	NOUN
ajst-22330	106	21	for	for	ADP
ajst-22330	106	22	unsupervised	unsupervised	ADJ
ajst-22330	106	23	representation	representation	NOUN
ajst-22330	106	24	learning[j	learning[j	NOUN
ajst-22330	106	25	]	]	PUNCT
ajst-22330	106	26	.	.	PUNCT
ajst-22330	107	1	arxiv	arxiv	PROPN
ajst-22330	107	2	preprint	preprint	VERB
ajst-22330	107	3	arxiv:1804.00222	arxiv:1804.00222	NOUN
ajst-22330	107	4	,	,	PUNCT
ajst-22330	107	5	2018	2018	NUM
ajst-22330	107	6	.	.	PUNCT
ajst-22330	108	1	[	[	X
ajst-22330	108	2	13	13	NUM
ajst-22330	108	3	]	]	X
ajst-22330	108	4	andrychowicz	andrychowicz	PROPN
ajst-22330	108	5	m	m	PROPN
ajst-22330	108	6	,	,	PUNCT
ajst-22330	108	7	denil	denil	PROPN
ajst-22330	108	8	m	m	PROPN
ajst-22330	108	9	,	,	PUNCT
ajst-22330	108	10	gomez	gomez	PROPN
ajst-22330	108	11	s	s	PROPN
ajst-22330	108	12	,	,	PUNCT
ajst-22330	108	13	et	et	PROPN
ajst-22330	108	14	al	al	PROPN
ajst-22330	108	15	.	.	PUNCT
ajst-22330	109	1	learning	learn	VERB
ajst-22330	109	2	to	to	PART
ajst-22330	109	3	learn	learn	VERB
ajst-22330	109	4	by	by	ADP
ajst-22330	109	5	gradient	gradient	ADJ
ajst-22330	109	6	descent	descent	NOUN
ajst-22330	109	7	by	by	ADP
ajst-22330	109	8	gradient	gradient	NOUN
ajst-22330	109	9	descent[j	descent[j	PROPN
ajst-22330	109	10	]	]	PUNCT
ajst-22330	109	11	.	.	PUNCT
ajst-22330	110	1	advances	advance	NOUN
ajst-22330	110	2	in	in	ADP
ajst-22330	110	3	neural	neural	ADJ
ajst-22330	110	4	information	information	NOUN
ajst-22330	110	5	processing	processing	NOUN
ajst-22330	110	6	systems	system	NOUN
ajst-22330	110	7	,	,	PUNCT
ajst-22330	110	8	2016	2016	NUM
ajst-22330	110	9	,	,	PUNCT
ajst-22330	110	10	29	29	NUM
ajst-22330	110	11	.	.	PUNCT
ajst-22330	111	1	[	[	X
ajst-22330	111	2	14	14	NUM
ajst-22330	111	3	]	]	X
ajst-22330	111	4	finn	finn	PROPN
ajst-22330	111	5	c	c	PROPN
ajst-22330	111	6	,	,	PUNCT
ajst-22330	111	7	abbeel	abbeel	NOUN
ajst-22330	111	8	p	p	PROPN
ajst-22330	111	9	,	,	PUNCT
ajst-22330	111	10	levine	levine	PROPN
ajst-22330	111	11	s.	s.	PROPN
ajst-22330	111	12	model	model	PROPN
ajst-22330	111	13	-	-	PUNCT
ajst-22330	111	14	agnostic	agnostic	ADJ
ajst-22330	111	15	meta	meta	NOUN
ajst-22330	111	16	-	-	PUNCT
ajst-22330	111	17	learning	learning	NOUN
ajst-22330	111	18	for	for	ADP
ajst-22330	111	19	fast	fast	ADJ
ajst-22330	111	20	adaptation	adaptation	NOUN
ajst-22330	111	21	of	of	ADP
ajst-22330	111	22	deep	deep	ADJ
ajst-22330	111	23	networks[c	networks[c	PROPN
ajst-22330	111	24	]	]	PUNCT
ajst-22330	111	25	.	.	PUNCT
ajst-22330	112	1	international	international	ADJ
ajst-22330	112	2	conference	conference	NOUN
ajst-22330	112	3	on	on	ADP
ajst-22330	112	4	machine	machine	NOUN
ajst-22330	112	5	learning	learning	NOUN
ajst-22330	112	6	.	.	PUNCT
ajst-22330	113	1	2017	2017	NUM
ajst-22330	113	2	:	:	PUNCT
ajst-22330	113	3	1126	1126	NUM
ajst-22330	113	4	-	-	SYM
ajst-22330	113	5	1135	1135	NUM
ajst-22330	113	6	.	.	PUNCT
ajst-22330	114	1	[	[	X
ajst-22330	114	2	15	15	NUM
ajst-22330	114	3	]	]	X
ajst-22330	114	4	donahue	donahue	PROPN
ajst-22330	114	5	j	j	PROPN
ajst-22330	114	6	,	,	PUNCT
ajst-22330	114	7	jia	jia	PROPN
ajst-22330	114	8	y	y	PROPN
ajst-22330	114	9	,	,	PUNCT
ajst-22330	114	10	vinyals	vinyal	NOUN
ajst-22330	114	11	o	o	NOUN
ajst-22330	114	12	,	,	PUNCT
ajst-22330	114	13	et	et	PROPN
ajst-22330	114	14	al	al	PROPN
ajst-22330	114	15	.	.	PROPN
ajst-22330	114	16	decaf	decaf	PROPN
ajst-22330	114	17	:	:	PUNCT
ajst-22330	114	18	a	a	DET
ajst-22330	114	19	deep	deep	ADJ
ajst-22330	114	20	convolutional	convolutional	ADJ
ajst-22330	114	21	activation	activation	NOUN
ajst-22330	114	22	feature	feature	NOUN
ajst-22330	114	23	for	for	ADP
ajst-22330	114	24	generic	generic	ADJ
ajst-22330	114	25	visual	visual	ADJ
ajst-22330	114	26	recognition[c	recognition[c	PROPN
ajst-22330	114	27	]	]	PUNCT
ajst-22330	114	28	.	.	PUNCT
ajst-22330	115	1	international	international	ADJ
ajst-22330	115	2	conference	conference	NOUN
ajst-22330	115	3	on	on	ADP
ajst-22330	115	4	machine	machine	NOUN
ajst-22330	115	5	learning	learning	NOUN
ajst-22330	115	6	.	.	PUNCT
ajst-22330	116	1	2014	2014	NUM
ajst-22330	116	2	:	:	PUNCT
ajst-22330	117	1	647	647	NUM
ajst-22330	117	2	-	-	SYM
ajst-22330	117	3	655	655	NUM
ajst-22330	117	4	.	.	PUNCT
ajst-22330	118	1	[	[	X
ajst-22330	118	2	16	16	NUM
ajst-22330	118	3	]	]	PUNCT
ajst-22330	118	4	obamuyide	obamuyide	NOUN
ajst-22330	118	5	a	a	PRON
ajst-22330	118	6	,	,	PUNCT
ajst-22330	118	7	vlachos	vlachos	PROPN
ajst-22330	118	8	a.	a.	NOUN
ajst-22330	118	9	model	model	PROPN
ajst-22330	118	10	-	-	PUNCT
ajst-22330	118	11	agnostic	agnostic	ADJ
ajst-22330	118	12	meta	meta	NOUN
ajst-22330	118	13	-	-	PUNCT
ajst-22330	118	14	learning	learning	NOUN
ajst-22330	118	15	for	for	ADP
ajst-22330	118	16	relation	relation	NOUN
ajst-22330	118	17	classification	classification	NOUN
ajst-22330	118	18	with	with	ADP
ajst-22330	118	19	limited	limited	ADJ
ajst-22330	118	20	supervision[c	supervision[c	NOUN
ajst-22330	118	21	]	]	PUNCT
ajst-22330	118	22	.	.	PUNCT
ajst-22330	119	1	proceedings	proceeding	NOUN
ajst-22330	119	2	of	of	ADP
ajst-22330	119	3	the	the	DET
ajst-22330	119	4	57th	57th	ADJ
ajst-22330	119	5	annual	annual	ADJ
ajst-22330	119	6	meeting	meeting	NOUN
ajst-22330	119	7	of	of	ADP
ajst-22330	119	8	the	the	DET
ajst-22330	119	9	association	association	NOUN
ajst-22330	119	10	for	for	ADP
ajst-22330	119	11	computational	computational	ADJ
ajst-22330	119	12	linguistics	linguistic	NOUN
ajst-22330	119	13	.	.	PUNCT
ajst-22330	120	1	2019	2019	NUM
ajst-22330	120	2	:	:	PUNCT
ajst-22330	120	3	5873	5873	NUM
ajst-22330	120	4	-	-	SYM
ajst-22330	120	5	5879	5879	NUM
ajst-22330	120	6	.	.	PUNCT
ajst-22330	121	1	[	[	X
ajst-22330	121	2	17	17	NUM
ajst-22330	121	3	]	]	X
ajst-22330	121	4	chen	chen	PROPN
ajst-22330	121	5	f	f	PROPN
ajst-22330	121	6	,	,	PUNCT
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ajst-22330	121	12	,	,	PUNCT
ajst-22330	121	13	et	et	PROPN
ajst-22330	121	14	al	al	PROPN
ajst-22330	121	15	.	.	PROPN
ajst-22330	121	16	federated	federate	VERB
ajst-22330	121	17	meta	meta	ADV
ajst-22330	121	18	-	-	PUNCT
ajst-22330	121	19	learning	learning	NOUN
ajst-22330	121	20	with	with	ADP
ajst-22330	121	21	fast	fast	ADJ
ajst-22330	121	22	convergence	convergence	NOUN
ajst-22330	121	23	and	and	CCONJ
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ajst-22330	121	25	communication[j	communication[j	NOUN
ajst-22330	121	26	]	]	PUNCT
ajst-22330	121	27	.	.	PUNCT
ajst-22330	122	1	arxiv	arxiv	PROPN
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ajst-22330	122	6	.	.	PUNCT
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ajst-22330	123	5	m	m	PROPN
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ajst-22330	123	8	m	m	PROPN
ajst-22330	123	9	f	f	PROPN
ajst-22330	123	10	f	f	PROPN
ajst-22330	123	11	,	,	PUNCT
ajst-22330	123	12	talwalkar	talwalkar	PROPN
ajst-22330	123	13	a	a	DET
ajst-22330	123	14	s.	s.	PROPN
ajst-22330	123	15	adaptive	adaptive	PROPN
ajst-22330	123	16	gradientbased	gradientbase	VERB
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ajst-22330	123	18	-	-	PUNCT
ajst-22330	123	19	learning	learn	VERB
ajst-22330	123	20	methods[j	methods[j	NOUN
ajst-22330	123	21	]	]	PUNCT
ajst-22330	123	22	.	.	PUNCT
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ajst-22330	124	4	information	information	NOUN
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ajst-22330	124	6	systems	system	NOUN
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ajst-22330	124	9	,	,	PUNCT
ajst-22330	124	10	32	32	NUM
ajst-22330	124	11	.	.	PUNCT
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ajst-22330	125	3	]	]	PUNCT
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ajst-22330	125	6	,	,	PUNCT
ajst-22330	125	7	mokhtari	mokhtari	PROPN
ajst-22330	125	8	a	a	DET
ajst-22330	125	9	,	,	PUNCT
ajst-22330	125	10	ozdaglar	ozdaglar	ADJ
ajst-22330	125	11	a.	a.	NOUN
ajst-22330	125	12	personalized	personalize	VERB
ajst-22330	125	13	federated	federated	ADJ
ajst-22330	125	14	learning	learning	NOUN
ajst-22330	125	15	:	:	PUNCT
ajst-22330	125	16	a	a	DET
ajst-22330	125	17	meta	meta	ADV
ajst-22330	125	18	-	-	PUNCT
ajst-22330	125	19	learning	learn	VERB
ajst-22330	125	20	approach[j	approach[j	NOUN
ajst-22330	125	21	]	]	PUNCT
ajst-22330	125	22	.	.	PUNCT
ajst-22330	126	1	arxiv	arxiv	PROPN
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ajst-22330	126	4	,	,	PUNCT
ajst-22330	126	5	2020	2020	NUM
ajst-22330	126	6	.	.	PUNCT
ajst-22330	127	1	[	[	X
ajst-22330	127	2	20	20	NUM
ajst-22330	127	3	]	]	X
ajst-22330	127	4	kayaalp	kayaalp	PROPN
ajst-22330	127	5	m	m	PROPN
ajst-22330	127	6	,	,	PUNCT
ajst-22330	127	7	vlaski	vlaski	VERB
ajst-22330	127	8	s	s	PROPN
ajst-22330	127	9	,	,	PUNCT
ajst-22330	127	10	sayed	say	VERB
ajst-22330	127	11	a	a	DET
ajst-22330	127	12	h.	h.	PROPN
ajst-22330	127	13	dif	dif	X
ajst-22330	127	14	-	-	PUNCT
ajst-22330	127	15	maml	maml	PROPN
ajst-22330	127	16	:	:	PUNCT
ajst-22330	127	17	decentralized	decentralize	VERB
ajst-22330	127	18	multi	multi	ADJ
ajst-22330	127	19	-	-	ADJ
ajst-22330	127	20	agent	agent	ADJ
ajst-22330	127	21	meta	meta	NOUN
ajst-22330	127	22	-	-	NOUN
ajst-22330	127	23	learning[j	learning[j	NOUN
ajst-22330	127	24	]	]	PUNCT
ajst-22330	127	25	.	.	PUNCT
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ajst-22330	128	6	processing	processing	NOUN
ajst-22330	128	7	,	,	PUNCT
ajst-22330	128	8	2022	2022	NUM
ajst-22330	128	9	,	,	PUNCT
ajst-22330	128	10	3	3	NUM
ajst-22330	128	11	:	:	SYM
ajst-22330	128	12	71	71	NUM
ajst-22330	128	13	-	-	SYM
ajst-22330	128	14	93	93	NUM
ajst-22330	128	15	.	.	PUNCT
ajst-22330	129	1	[	[	X
ajst-22330	129	2	21	21	NUM
ajst-22330	129	3	]	]	X
ajst-22330	129	4	mendieta	mendieta	PROPN
ajst-22330	129	5	m	m	PROPN
ajst-22330	129	6	,	,	PUNCT
ajst-22330	129	7	yang	yang	PROPN
ajst-22330	129	8	t	t	PROPN
ajst-22330	129	9	,	,	PUNCT
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ajst-22330	129	13	et	et	PROPN
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ajst-22330	130	4	:	:	PUNCT
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ajst-22330	130	8	in	in	ADP
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ajst-22330	130	10	learning[c	learning[c	NOUN
ajst-22330	130	11	]	]	PUNCT
ajst-22330	130	12	.	.	PUNCT
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ajst-22330	131	4	ieee	ieee	NOUN
ajst-22330	131	5	/	/	SYM
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ajst-22330	131	7	conference	conference	NOUN
ajst-22330	131	8	on	on	ADP
ajst-22330	131	9	computer	computer	NOUN
ajst-22330	131	10	vision	vision	NOUN
ajst-22330	131	11	and	and	CCONJ
ajst-22330	131	12	pattern	pattern	NOUN
ajst-22330	131	13	recognition	recognition	NOUN
ajst-22330	131	14	.	.	PUNCT
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ajst-22330	132	6	.	.	PUNCT
ajst-22330	133	1	[	[	X
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ajst-22330	133	3	]	]	PUNCT
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ajst-22330	133	6	,	,	PUNCT
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ajst-22330	133	15	federated	federated	ADJ
ajst-22330	133	16	learning	learning	NOUN
ajst-22330	133	17	by	by	ADP
ajst-22330	133	18	seeking	seek	VERB
ajst-22330	133	19	flat	flat	ADJ
ajst-22330	133	20	minima[c	minima[c	NOUN
ajst-22330	133	21	]	]	PUNCT
ajst-22330	133	22	.	.	PUNCT
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ajst-22330	134	6	.	.	PUNCT
ajst-22330	135	1	cham	cham	PROPN
ajst-22330	135	2	:	:	PUNCT
ajst-22330	135	3	springer	springer	NOUN
ajst-22330	135	4	nature	nature	PROPN
ajst-22330	135	5	switzerland	switzerland	PROPN
ajst-22330	135	6	,	,	PUNCT
ajst-22330	135	7	2022	2022	NUM
ajst-22330	135	8	:	:	PUNCT
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ajst-22330	135	10	-	-	SYM
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ajst-22330	135	12	.	.	PUNCT
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ajst-22330	136	3	]	]	X
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ajst-22330	136	5	p	p	X
ajst-22330	136	6	,	,	PUNCT
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ajst-22330	136	9	,	,	PUNCT
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ajst-22330	136	12	,	,	PUNCT
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ajst-22330	136	17	-	-	PUNCT
ajst-22330	136	18	sgd	sgd	NOUN
ajst-22330	136	19	:	:	PUNCT
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ajst-22330	136	23	into	into	ADP
ajst-22330	136	24	wide	wide	ADJ
ajst-22330	136	25	valleys[j	valleys[j	PROPN
ajst-22330	136	26	]	]	PUNCT
ajst-22330	136	27	.	.	PUNCT
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ajst-22330	137	3	statistical	statistical	ADJ
ajst-22330	137	4	mechanics	mechanic	NOUN
ajst-22330	137	5	:	:	PUNCT
ajst-22330	137	6	theory	theory	NOUN
ajst-22330	137	7	and	and	CCONJ
ajst-22330	137	8	experiment	experiment	NOUN
ajst-22330	137	9	,	,	PUNCT
ajst-22330	137	10	2019	2019	NUM
ajst-22330	137	11	,	,	PUNCT
ajst-22330	137	12	2019(12	2019(12	NUM
ajst-22330	137	13	):	):	PUNCT
ajst-22330	137	14	124018	124018	NUM
ajst-22330	137	15	.	.	PUNCT
ajst-22330	138	1	[	[	X
ajst-22330	138	2	24	24	NUM
ajst-22330	138	3	]	]	PUNCT
ajst-22330	138	4	izmailov	izmailov	NOUN
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ajst-22330	138	9	,	,	PUNCT
ajst-22330	138	10	garipov	garipov	PROPN
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ajst-22330	138	12	,	,	PUNCT
ajst-22330	138	13	et	et	PROPN
ajst-22330	138	14	al	al	PROPN
ajst-22330	138	15	.	.	PUNCT
ajst-22330	139	1	averaging	average	VERB
ajst-22330	139	2	weights	weight	NOUN
ajst-22330	139	3	leads	lead	VERB
ajst-22330	139	4	to	to	ADP
ajst-22330	139	5	wider	wide	ADJ
ajst-22330	139	6	optima	optima	NOUN
ajst-22330	139	7	and	and	CCONJ
ajst-22330	139	8	better	well	ADJ
ajst-22330	139	9	generalization[j	generalization[j	X
ajst-22330	139	10	]	]	X
ajst-22330	139	11	.	.	PUNCT
ajst-22330	140	1	arxiv	arxiv	PROPN
ajst-22330	140	2	preprint	preprint	NOUN
ajst-22330	140	3	arxiv:1803.05407	arxiv:1803.05407	NOUN
ajst-22330	140	4	,	,	PUNCT
ajst-22330	140	5	2018	2018	NUM
ajst-22330	140	6	.	.	PUNCT
ajst-22330	141	1	[	[	X
ajst-22330	141	2	25	25	NUM
ajst-22330	141	3	]	]	PUNCT
ajst-22330	141	4	foret	foret	NOUN
ajst-22330	141	5	p	p	PROPN
ajst-22330	141	6	,	,	PUNCT
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ajst-22330	141	9	,	,	PUNCT
ajst-22330	141	10	mobahi	mobahi	NOUN
ajst-22330	141	11	h	h	NOUN
ajst-22330	141	12	,	,	PUNCT
ajst-22330	141	13	et	et	PROPN
ajst-22330	141	14	al	al	PROPN
ajst-22330	141	15	.	.	PROPN
ajst-22330	141	16	sharpness	sharpness	NOUN
ajst-22330	141	17	-	-	PUNCT
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ajst-22330	141	19	minimization	minimization	NOUN
ajst-22330	141	20	for	for	ADP
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ajst-22330	141	22	improving	improve	VERB
ajst-22330	141	23	generalization[j	generalization[j	PROPN
ajst-22330	141	24	]	]	PUNCT
ajst-22330	141	25	.	.	PUNCT
ajst-22330	142	1	arxiv	arxiv	PROPN
ajst-22330	142	2	preprint	preprint	PROPN
ajst-22330	142	3	arxiv:2010.01412	arxiv:2010.01412	NOUN
ajst-22330	142	4	,	,	PUNCT
ajst-22330	142	5	2020	2020	NUM
ajst-22330	142	6	.	.	PUNCT