id	sid	tid	token	lemma	pos
ajst-32396	1	1	224	224	NUM
ajst-32396	1	2	a	a	DET
ajst-32396	1	3	comprehensive	comprehensive	ADJ
ajst-32396	1	4	review	review	NOUN
ajst-32396	1	5	of	of	ADP
ajst-32396	1	6	principal	principal	ADJ
ajst-32396	1	7	component	component	NOUN
ajst-32396	1	8	analysis	analysis	NOUN
ajst-32396	1	9	yubo	yubo	VERB
ajst-32396	1	10	ye	ye	PROPN
ajst-32396	1	11	*	*	PUNCT
ajst-32396	1	12	department	department	PROPN
ajst-32396	1	13	of	of	ADP
ajst-32396	1	14	mathematics	mathematics	PROPN
ajst-32396	1	15	,	,	PUNCT
ajst-32396	1	16	university	university	NOUN
ajst-32396	1	17	college	college	PROPN
ajst-32396	1	18	london	london	PROPN
ajst-32396	1	19	,	,	PUNCT
ajst-32396	1	20	uk	uk	PROPN
ajst-32396	1	21	*	*	PUNCT
ajst-32396	1	22	corresponding	correspond	VERB
ajst-32396	1	23	author	author	NOUN
ajst-32396	1	24	email	email	NOUN
ajst-32396	1	25	:	:	PUNCT
ajst-32396	1	26	yubo.ye.24@ucl.ac.uk	yubo.ye.24@ucl.ac.uk	PROPN
ajst-32396	1	27	abstract	abstract	NOUN
ajst-32396	1	28	.	.	PUNCT
ajst-32396	2	1	pca	pca	NOUN
ajst-32396	2	2	(	(	PUNCT
ajst-32396	2	3	principal	principal	ADJ
ajst-32396	2	4	component	component	NOUN
ajst-32396	2	5	analysis	analysis	NOUN
ajst-32396	2	6	)	)	PUNCT
ajst-32396	2	7	is	be	AUX
ajst-32396	2	8	a	a	DET
ajst-32396	2	9	method	method	NOUN
ajst-32396	2	10	aiming	aim	VERB
ajst-32396	2	11	to	to	PART
ajst-32396	2	12	reduce	reduce	VERB
ajst-32396	2	13	the	the	DET
ajst-32396	2	14	dimensions	dimension	NOUN
ajst-32396	2	15	among	among	ADP
ajst-32396	2	16	data	datum	NOUN
ajst-32396	2	17	analysis	analysis	NOUN
ajst-32396	2	18	,	,	PUNCT
ajst-32396	2	19	with	with	ADP
ajst-32396	2	20	various	various	ADJ
ajst-32396	2	21	applications	application	NOUN
ajst-32396	2	22	in	in	ADP
ajst-32396	2	23	neurosciences	neuroscience	NOUN
ajst-32396	2	24	,	,	PUNCT
ajst-32396	2	25	finance	finance	NOUN
ajst-32396	2	26	,	,	PUNCT
ajst-32396	2	27	and	and	CCONJ
ajst-32396	2	28	beyond	beyond	ADP
ajst-32396	2	29	.	.	PUNCT
ajst-32396	3	1	data	datum	NOUN
ajst-32396	3	2	normalization	normalization	NOUN
ajst-32396	3	3	,	,	PUNCT
ajst-32396	3	4	covariance	covariance	NOUN
ajst-32396	3	5	matrix	matrix	NOUN
ajst-32396	3	6	decomposition	decomposition	NOUN
ajst-32396	3	7	,	,	PUNCT
ajst-32396	3	8	eigenvalue	eigenvalue	NOUN
ajst-32396	3	9	-	-	PUNCT
ajst-32396	3	10	driven	drive	VERB
ajst-32396	3	11	component	component	NOUN
ajst-32396	3	12	selection	selection	NOUN
ajst-32396	3	13	,	,	PUNCT
ajst-32396	3	14	and	and	CCONJ
ajst-32396	3	15	other	other	ADJ
ajst-32396	3	16	mathematical	mathematical	ADJ
ajst-32396	3	17	underpinnings	underpinning	NOUN
ajst-32396	3	18	of	of	ADP
ajst-32396	3	19	pca	pca	NOUN
ajst-32396	3	20	will	will	AUX
ajst-32396	3	21	be	be	AUX
ajst-32396	3	22	methodically	methodically	ADV
ajst-32396	3	23	covered	cover	VERB
ajst-32396	3	24	in	in	ADP
ajst-32396	3	25	this	this	DET
ajst-32396	3	26	article	article	NOUN
ajst-32396	3	27	.	.	PUNCT
ajst-32396	4	1	a	a	DET
ajst-32396	4	2	comparison	comparison	NOUN
ajst-32396	4	3	with	with	ADP
ajst-32396	4	4	svd	svd	PROPN
ajst-32396	4	5	decomposition	decomposition	NOUN
ajst-32396	4	6	will	will	AUX
ajst-32396	4	7	also	also	ADV
ajst-32396	4	8	be	be	AUX
ajst-32396	4	9	made	make	VERB
ajst-32396	4	10	due	due	ADJ
ajst-32396	4	11	to	to	ADP
ajst-32396	4	12	the	the	DET
ajst-32396	4	13	similarities	similarity	NOUN
ajst-32396	4	14	between	between	ADP
ajst-32396	4	15	the	the	DET
ajst-32396	4	16	two	two	NUM
ajst-32396	4	17	methods	method	NOUN
ajst-32396	4	18	.	.	PUNCT
ajst-32396	5	1	additionally	additionally	ADV
ajst-32396	5	2	,	,	PUNCT
ajst-32396	5	3	we	we	PRON
ajst-32396	5	4	will	will	AUX
ajst-32396	5	5	discuss	discuss	VERB
ajst-32396	5	6	contemporary	contemporary	ADJ
ajst-32396	5	7	developments	development	NOUN
ajst-32396	5	8	like	like	ADP
ajst-32396	5	9	sparse	sparse	ADJ
ajst-32396	5	10	pca	pca	PROPN
ajst-32396	5	11	,	,	PUNCT
ajst-32396	5	12	kernel	kernel	PROPN
ajst-32396	5	13	pca	pca	PROPN
ajst-32396	5	14	,	,	PUNCT
ajst-32396	5	15	and	and	CCONJ
ajst-32396	5	16	robust	robust	ADJ
ajst-32396	5	17	pca	pca	NOUN
ajst-32396	5	18	that	that	PRON
ajst-32396	5	19	tackle	tackle	VERB
ajst-32396	5	20	nonlinearity	nonlinearity	NOUN
ajst-32396	5	21	and	and	CCONJ
ajst-32396	5	22	sparsity	sparsity	NOUN
ajst-32396	5	23	by	by	ADP
ajst-32396	5	24	integrating	integrate	VERB
ajst-32396	5	25	trends	trend	NOUN
ajst-32396	5	26	like	like	ADP
ajst-32396	5	27	pca	pca	PROPN
ajst-32396	5	28	's	's	PART
ajst-32396	5	29	integration	integration	NOUN
ajst-32396	5	30	with	with	ADP
ajst-32396	5	31	deep	deep	ADJ
ajst-32396	5	32	learning	learning	NOUN
ajst-32396	5	33	,	,	PUNCT
ajst-32396	5	34	the	the	DET
ajst-32396	5	35	variation	variation	NOUN
ajst-32396	5	36	in	in	ADP
ajst-32396	5	37	applied	applied	ADJ
ajst-32396	5	38	circumstances	circumstance	NOUN
ajst-32396	5	39	,	,	PUNCT
ajst-32396	5	40	and	and	CCONJ
ajst-32396	5	41	its	its	PRON
ajst-32396	5	42	use	use	NOUN
ajst-32396	5	43	in	in	ADP
ajst-32396	5	44	high	high	ADJ
ajst-32396	5	45	-	-	PUNCT
ajst-32396	5	46	dimensional	dimensional	ADJ
ajst-32396	5	47	data	datum	NOUN
ajst-32396	5	48	presentation	presentation	NOUN
ajst-32396	5	49	.	.	PUNCT
ajst-32396	6	1	furthermore	furthermore	ADV
ajst-32396	6	2	,	,	PUNCT
ajst-32396	6	3	this	this	DET
ajst-32396	6	4	review	review	NOUN
ajst-32396	6	5	will	will	AUX
ajst-32396	6	6	also	also	ADV
ajst-32396	6	7	highlight	highlight	VERB
ajst-32396	6	8	the	the	DET
ajst-32396	6	9	inherent	inherent	ADJ
ajst-32396	6	10	limits	limit	NOUN
ajst-32396	6	11	,	,	PUNCT
ajst-32396	6	12	such	such	ADJ
ajst-32396	6	13	as	as	ADP
ajst-32396	6	14	nonlinearity	nonlinearity	NOUN
ajst-32396	6	15	issues	issue	NOUN
ajst-32396	6	16	,	,	PUNCT
ajst-32396	6	17	massive	massive	ADJ
ajst-32396	6	18	datasets	dataset	NOUN
ajst-32396	6	19	,	,	PUNCT
ajst-32396	6	20	and	and	CCONJ
ajst-32396	6	21	data	datum	NOUN
ajst-32396	6	22	contamination	contamination	NOUN
ajst-32396	6	23	.	.	PUNCT
ajst-32396	7	1	throughout	throughout	ADP
ajst-32396	7	2	investigation	investigation	NOUN
ajst-32396	7	3	,	,	PUNCT
ajst-32396	7	4	this	this	DET
ajst-32396	7	5	review	review	NOUN
ajst-32396	7	6	serves	serve	VERB
ajst-32396	7	7	as	as	ADP
ajst-32396	7	8	a	a	DET
ajst-32396	7	9	map	map	NOUN
ajst-32396	7	10	for	for	SCONJ
ajst-32396	7	11	the	the	DET
ajst-32396	7	12	researchers	researcher	NOUN
ajst-32396	7	13	tackling	tackle	VERB
ajst-32396	7	14	with	with	ADP
ajst-32396	7	15	increasingly	increasingly	ADV
ajst-32396	7	16	complex	complex	ADJ
ajst-32396	7	17	data	datum	NOUN
ajst-32396	7	18	environments	environment	NOUN
ajst-32396	7	19	requiring	require	VERB
ajst-32396	7	20	dimensionality	dimensionality	NOUN
ajst-32396	7	21	reduction	reduction	NOUN
ajst-32396	7	22	and	and	CCONJ
ajst-32396	7	23	are	be	AUX
ajst-32396	7	24	not	not	PART
ajst-32396	7	25	certain	certain	ADJ
ajst-32396	7	26	with	with	ADP
ajst-32396	7	27	the	the	DET
ajst-32396	7	28	specific	specific	ADJ
ajst-32396	7	29	pca	pca	NOUN
ajst-32396	7	30	type	type	NOUN
ajst-32396	7	31	selected	select	VERB
ajst-32396	7	32	to	to	PART
ajst-32396	7	33	apply	apply	VERB
ajst-32396	7	34	.	.	PUNCT
ajst-32396	8	1	keywords	keyword	NOUN
ajst-32396	8	2	:	:	PUNCT
ajst-32396	8	3	principal	principal	ADJ
ajst-32396	8	4	component	component	NOUN
ajst-32396	8	5	analysis	analysis	NOUN
ajst-32396	8	6	,	,	PUNCT
ajst-32396	8	7	dimensionality	dimensionality	NOUN
ajst-32396	8	8	reduction	reduction	NOUN
ajst-32396	8	9	,	,	PUNCT
ajst-32396	8	10	correlation	correlation	NOUN
ajst-32396	8	11	variance	variance	NOUN
ajst-32396	8	12	,	,	PUNCT
ajst-32396	8	13	data	datum	NOUN
ajst-32396	8	14	analysis	analysis	NOUN
ajst-32396	8	15	,	,	PUNCT
ajst-32396	8	16	kernel	kernel	PROPN
ajst-32396	8	17	pca	pca	PROPN
ajst-32396	8	18	.	.	PROPN
ajst-32396	9	1	1	1	X
ajst-32396	9	2	.	.	X
ajst-32396	9	3	introduction	introduction	NOUN
ajst-32396	9	4	pca	pca	PROPN
ajst-32396	9	5	was	be	AUX
ajst-32396	9	6	first	first	ADV
ajst-32396	9	7	introduced	introduce	VERB
ajst-32396	9	8	by	by	ADP
ajst-32396	9	9	karl	karl	PROPN
ajst-32396	9	10	pearson	pearson	PROPN
ajst-32396	9	11	in	in	ADP
ajst-32396	9	12	1901	1901	NUM
ajst-32396	9	13	,	,	PUNCT
ajst-32396	9	14	is	be	AUX
ajst-32396	9	15	to	to	PART
ajst-32396	9	16	reduce	reduce	VERB
ajst-32396	9	17	the	the	DET
ajst-32396	9	18	dimensionality	dimensionality	NOUN
ajst-32396	9	19	of	of	ADP
ajst-32396	9	20	a	a	DET
ajst-32396	9	21	data	datum	NOUN
ajst-32396	9	22	set	set	VERB
ajst-32396	9	23	retaining	retain	VERB
ajst-32396	9	24	as	as	ADV
ajst-32396	9	25	much	much	ADV
ajst-32396	9	26	as	as	ADP
ajst-32396	9	27	possible	possible	ADJ
ajst-32396	9	28	of	of	ADP
ajst-32396	9	29	the	the	DET
ajst-32396	9	30	variation	variation	NOUN
ajst-32396	9	31	[	[	X
ajst-32396	9	32	1	1	NUM
ajst-32396	9	33	]	]	PUNCT
ajst-32396	9	34	.	.	PUNCT
ajst-32396	10	1	the	the	DET
ajst-32396	10	2	pca	pca	PROPN
ajst-32396	10	3	method	method	NOUN
ajst-32396	10	4	could	could	AUX
ajst-32396	10	5	efficiently	efficiently	ADV
ajst-32396	10	6	exclude	exclude	VERB
ajst-32396	10	7	redundant	redundant	ADJ
ajst-32396	10	8	data	datum	NOUN
ajst-32396	10	9	and	and	CCONJ
ajst-32396	10	10	extract	extract	VERB
ajst-32396	10	11	the	the	DET
ajst-32396	10	12	most	most	ADV
ajst-32396	10	13	important	important	ADJ
ajst-32396	10	14	information	information	NOUN
ajst-32396	10	15	,	,	PUNCT
ajst-32396	10	16	which	which	PRON
ajst-32396	10	17	preserves	preserve	VERB
ajst-32396	10	18	two	two	NUM
ajst-32396	10	19	goals	goal	NOUN
ajst-32396	10	20	:	:	PUNCT
ajst-32396	10	21	preserving	preserve	VERB
ajst-32396	10	22	maximal	maximal	ADJ
ajst-32396	10	23	variance	variance	NOUN
ajst-32396	10	24	in	in	ADP
ajst-32396	10	25	the	the	DET
ajst-32396	10	26	data	datum	NOUN
ajst-32396	10	27	with	with	ADP
ajst-32396	10	28	the	the	DET
ajst-32396	10	29	least	least	ADJ
ajst-32396	10	30	dimensions	dimension	NOUN
ajst-32396	10	31	as	as	ADV
ajst-32396	10	32	well	well	ADV
ajst-32396	10	33	as	as	ADP
ajst-32396	10	34	enabling	enable	VERB
ajst-32396	10	35	the	the	DET
ajst-32396	10	36	presentations	presentation	NOUN
ajst-32396	10	37	of	of	ADP
ajst-32396	10	38	complex	complex	ADJ
ajst-32396	10	39	structures	structure	NOUN
ajst-32396	10	40	.	.	PUNCT
ajst-32396	11	1	despite	despite	SCONJ
ajst-32396	11	2	its	its	PRON
ajst-32396	11	3	simplicity	simplicity	NOUN
ajst-32396	11	4	,	,	PUNCT
ajst-32396	11	5	pca	pca	PROPN
ajst-32396	11	6	has	have	VERB
ajst-32396	11	7	numerous	numerous	ADJ
ajst-32396	11	8	extensions	extension	NOUN
ajst-32396	11	9	in	in	ADP
ajst-32396	11	10	addressing	address	VERB
ajst-32396	11	11	distinctive	distinctive	ADJ
ajst-32396	11	12	challenges	challenge	NOUN
ajst-32396	11	13	.	.	PUNCT
ajst-32396	12	1	by	by	ADP
ajst-32396	12	2	using	use	VERB
ajst-32396	12	3	a	a	DET
ajst-32396	12	4	nonlinear	nonlinear	ADJ
ajst-32396	12	5	map	map	NOUN
ajst-32396	12	6	to	to	PART
ajst-32396	12	7	relate	relate	VERB
ajst-32396	12	8	high	high	ADJ
ajst-32396	12	9	-	-	PUNCT
ajst-32396	12	10	dimensional	dimensional	ADJ
ajst-32396	12	11	feature	feature	NOUN
ajst-32396	12	12	spaces	space	NOUN
ajst-32396	12	13	to	to	ADP
ajst-32396	12	14	the	the	DET
ajst-32396	12	15	input	input	NOUN
ajst-32396	12	16	space	space	NOUN
ajst-32396	12	17	,	,	PUNCT
ajst-32396	12	18	kernel	kernel	PROPN
ajst-32396	12	19	pca	pca	PROPN
ajst-32396	12	20	utilizes	utilizes	PROPN
ajst-32396	12	21	kernel	kernel	PROPN
ajst-32396	12	22	functions	function	NOUN
ajst-32396	12	23	to	to	PART
ajst-32396	12	24	compute	compute	VERB
ajst-32396	12	25	the	the	DET
ajst-32396	12	26	principal	principal	ADJ
ajst-32396	12	27	components	component	NOUN
ajst-32396	12	28	in	in	ADP
ajst-32396	12	29	these	these	DET
ajst-32396	12	30	spaces	space	NOUN
ajst-32396	12	31	[	[	X
ajst-32396	12	32	2	2	NUM
ajst-32396	12	33	]	]	PUNCT
ajst-32396	12	34	,	,	PUNCT
ajst-32396	12	35	provides	provide	VERB
ajst-32396	12	36	a	a	DET
ajst-32396	12	37	feasible	feasible	ADJ
ajst-32396	12	38	way	way	NOUN
ajst-32396	12	39	to	to	ADP
ajst-32396	12	40	nonlinear	nonlinear	ADJ
ajst-32396	12	41	manifolds	manifold	NOUN
ajst-32396	12	42	.	.	PUNCT
ajst-32396	13	1	meanwhile	meanwhile	ADV
ajst-32396	13	2	,	,	PUNCT
ajst-32396	13	3	the	the	DET
ajst-32396	13	4	sparse	sparse	ADJ
ajst-32396	13	5	pca	pca	NOUN
ajst-32396	13	6	uses	use	VERB
ajst-32396	13	7	the	the	DET
ajst-32396	13	8	lasso	lasso	NOUN
ajst-32396	13	9	(	(	PUNCT
ajst-32396	13	10	elastic	elastic	ADJ
ajst-32396	13	11	net	net	NOUN
ajst-32396	13	12	)	)	PUNCT
ajst-32396	13	13	to	to	PART
ajst-32396	13	14	modify	modify	VERB
ajst-32396	13	15	the	the	DET
ajst-32396	13	16	principal	principal	ADJ
ajst-32396	13	17	components	component	NOUN
ajst-32396	13	18	with	with	ADP
ajst-32396	13	19	sparse	sparse	ADJ
ajst-32396	13	20	loadings	loading	NOUN
ajst-32396	13	21	[	[	X
ajst-32396	13	22	3	3	NUM
ajst-32396	13	23	]	]	PUNCT
ajst-32396	13	24	.	.	PUNCT
ajst-32396	14	1	not	not	PART
ajst-32396	14	2	to	to	PART
ajst-32396	14	3	mention	mention	VERB
ajst-32396	14	4	the	the	DET
ajst-32396	14	5	robust	robust	ADJ
ajst-32396	14	6	pca	pca	NOUN
ajst-32396	14	7	,	,	PUNCT
ajst-32396	14	8	where	where	SCONJ
ajst-32396	14	9	the	the	DET
ajst-32396	14	10	goal	goal	NOUN
ajst-32396	14	11	of	of	ADP
ajst-32396	14	12	mitigating	mitigate	VERB
ajst-32396	14	13	the	the	DET
ajst-32396	14	14	sensitivity	sensitivity	NOUN
ajst-32396	14	15	to	to	ADP
ajst-32396	14	16	outliers	outlier	NOUN
ajst-32396	14	17	is	be	AUX
ajst-32396	14	18	achieved	achieve	VERB
ajst-32396	14	19	.	.	PUNCT
ajst-32396	15	1	as	as	SCONJ
ajst-32396	15	2	the	the	DET
ajst-32396	15	3	datasets	dataset	NOUN
ajst-32396	15	4	grow	grow	VERB
ajst-32396	15	5	and	and	CCONJ
ajst-32396	15	6	complex	complex	ADJ
ajst-32396	15	7	,	,	PUNCT
ajst-32396	15	8	pca	pca	NOUN
ajst-32396	15	9	encounters	encounter	VERB
ajst-32396	15	10	limitations	limitation	NOUN
ajst-32396	15	11	such	such	ADJ
ajst-32396	15	12	as	as	ADP
ajst-32396	15	13	linearity	linearity	NOUN
ajst-32396	15	14	assumptions	assumption	NOUN
ajst-32396	15	15	,	,	PUNCT
ajst-32396	15	16	scalability	scalability	NOUN
ajst-32396	15	17	and	and	CCONJ
ajst-32396	15	18	interpretability	interpretability	NOUN
ajst-32396	15	19	.	.	PUNCT
ajst-32396	16	1	this	this	DET
ajst-32396	16	2	review	review	NOUN
ajst-32396	16	3	will	will	AUX
ajst-32396	16	4	conclude	conclude	VERB
ajst-32396	16	5	pca	pca	PROPN
ajst-32396	16	6	’s	’s	PART
ajst-32396	16	7	theoretical	theoretical	ADJ
ajst-32396	16	8	foundations	foundation	NOUN
ajst-32396	16	9	and	and	CCONJ
ajst-32396	16	10	potential	potential	ADJ
ajst-32396	16	11	applications	application	NOUN
ajst-32396	16	12	followed	follow	VERB
ajst-32396	16	13	by	by	ADP
ajst-32396	16	14	some	some	DET
ajst-32396	16	15	modern	modern	ADJ
ajst-32396	16	16	extensions	extension	NOUN
ajst-32396	16	17	and	and	CCONJ
ajst-32396	16	18	evaluations	evaluation	NOUN
ajst-32396	16	19	.	.	PUNCT
ajst-32396	17	1	in	in	ADP
ajst-32396	17	2	following	follow	VERB
ajst-32396	17	3	section	section	NOUN
ajst-32396	17	4	,	,	PUNCT
ajst-32396	17	5	we	we	PRON
ajst-32396	17	6	will	will	AUX
ajst-32396	17	7	discuss	discuss	VERB
ajst-32396	17	8	contemporary	contemporary	ADJ
ajst-32396	17	9	developments	development	NOUN
ajst-32396	17	10	like	like	ADP
ajst-32396	17	11	sparse	sparse	ADJ
ajst-32396	17	12	pca	pca	PROPN
ajst-32396	17	13	,	,	PUNCT
ajst-32396	17	14	kernel	kernel	PROPN
ajst-32396	17	15	pca	pca	PROPN
ajst-32396	17	16	,	,	PUNCT
ajst-32396	17	17	and	and	CCONJ
ajst-32396	17	18	robust	robust	ADJ
ajst-32396	17	19	pca	pca	NOUN
ajst-32396	17	20	that	that	PRON
ajst-32396	17	21	tackle	tackle	VERB
ajst-32396	17	22	nonlinearity	nonlinearity	NOUN
ajst-32396	17	23	and	and	CCONJ
ajst-32396	17	24	sparsity	sparsity	NOUN
ajst-32396	17	25	by	by	ADP
ajst-32396	17	26	integrating	integrate	VERB
ajst-32396	17	27	trends	trend	NOUN
ajst-32396	17	28	like	like	ADP
ajst-32396	17	29	pca	pca	PROPN
ajst-32396	17	30	's	's	PART
ajst-32396	17	31	integration	integration	NOUN
ajst-32396	17	32	with	with	ADP
ajst-32396	17	33	deep	deep	ADJ
ajst-32396	17	34	learning	learning	NOUN
ajst-32396	17	35	,	,	PUNCT
ajst-32396	17	36	the	the	DET
ajst-32396	17	37	variation	variation	NOUN
ajst-32396	17	38	in	in	ADP
ajst-32396	17	39	applied	applied	ADJ
ajst-32396	17	40	circumstances	circumstance	NOUN
ajst-32396	17	41	,	,	PUNCT
ajst-32396	17	42	and	and	CCONJ
ajst-32396	17	43	its	its	PRON
ajst-32396	17	44	use	use	NOUN
ajst-32396	17	45	in	in	ADP
ajst-32396	17	46	high	high	ADJ
ajst-32396	17	47	-	-	PUNCT
ajst-32396	17	48	dimensional	dimensional	ADJ
ajst-32396	17	49	data	datum	NOUN
ajst-32396	17	50	presentation	presentation	NOUN
ajst-32396	17	51	.	.	PUNCT
ajst-32396	18	1	furthermore	furthermore	ADV
ajst-32396	18	2	,	,	PUNCT
ajst-32396	18	3	this	this	DET
ajst-32396	18	4	review	review	NOUN
ajst-32396	18	5	will	will	AUX
ajst-32396	18	6	also	also	ADV
ajst-32396	18	7	highlight	highlight	VERB
ajst-32396	18	8	the	the	DET
ajst-32396	18	9	inherent	inherent	ADJ
ajst-32396	18	10	limits	limit	NOUN
ajst-32396	18	11	,	,	PUNCT
ajst-32396	18	12	such	such	ADJ
ajst-32396	18	13	as	as	ADP
ajst-32396	18	14	nonlinearity	nonlinearity	NOUN
ajst-32396	18	15	issues	issue	NOUN
ajst-32396	18	16	,	,	PUNCT
ajst-32396	18	17	massive	massive	ADJ
ajst-32396	18	18	datasets	dataset	NOUN
ajst-32396	18	19	,	,	PUNCT
ajst-32396	18	20	and	and	CCONJ
ajst-32396	18	21	data	datum	NOUN
ajst-32396	18	22	contamination	contamination	NOUN
ajst-32396	18	23	.	.	PUNCT
ajst-32396	19	1	2	2	X
ajst-32396	19	2	.	.	X
ajst-32396	19	3	mechanism	mechanism	NOUN
ajst-32396	19	4	of	of	ADP
ajst-32396	19	5	principle	principle	ADJ
ajst-32396	19	6	component	component	NOUN
ajst-32396	19	7	analysis	analysis	NOUN
ajst-32396	19	8	(	(	PUNCT
ajst-32396	19	9	pca	pca	PROPN
ajst-32396	19	10	)	)	PUNCT
ajst-32396	19	11	the	the	DET
ajst-32396	19	12	pca	pca	PROPN
ajst-32396	19	13	method	method	NOUN
ajst-32396	19	14	,	,	PUNCT
ajst-32396	19	15	considering	consider	VERB
ajst-32396	19	16	its	its	PRON
ajst-32396	19	17	nature	nature	NOUN
ajst-32396	19	18	of	of	ADP
ajst-32396	19	19	orthogonal	orthogonal	ADJ
ajst-32396	19	20	transformation	transformation	NOUN
ajst-32396	19	21	,	,	PUNCT
ajst-32396	19	22	could	could	AUX
ajst-32396	19	23	be	be	AUX
ajst-32396	19	24	achieved	achieve	VERB
ajst-32396	19	25	by	by	ADP
ajst-32396	19	26	linear	linear	PROPN
ajst-32396	19	27	transformation	transformation	NOUN
ajst-32396	19	28	,	,	PUNCT
ajst-32396	19	29	which	which	PRON
ajst-32396	19	30	is	be	AUX
ajst-32396	19	31	a	a	DET
ajst-32396	19	32	matrix	matrix	NOUN
ajst-32396	19	33	multiplication	multiplication	NOUN
ajst-32396	19	34	as	as	ADV
ajst-32396	19	35	well	well	ADV
ajst-32396	19	36	.	.	PUNCT
ajst-32396	20	1	among	among	ADP
ajst-32396	20	2	euclidean	euclidean	ADJ
ajst-32396	20	3	space	space	NOUN
ajst-32396	20	4	,	,	PUNCT
ajst-32396	20	5	the	the	DET
ajst-32396	20	6	maximization	maximization	NOUN
ajst-32396	20	7	of	of	ADP
ajst-32396	20	8	variance	variance	NOUN
ajst-32396	20	9	is	be	AUX
ajst-32396	20	10	executed	execute	VERB
ajst-32396	20	11	by	by	ADP
ajst-32396	20	12	the	the	DET
ajst-32396	20	13	algorithm	algorithm	NOUN
ajst-32396	20	14	combined	combine	VERB
ajst-32396	20	15	with	with	ADP
ajst-32396	20	16	singular	singular	ADJ
ajst-32396	20	17	value	value	NOUN
ajst-32396	20	18	decomposition	decomposition	NOUN
ajst-32396	20	19	(	(	PUNCT
ajst-32396	20	20	svd	svd	PROPN
ajst-32396	20	21	)	)	PUNCT
ajst-32396	20	22	method	method	NOUN
ajst-32396	20	23	.	.	PUNCT
ajst-32396	21	1	for	for	ADP
ajst-32396	21	2	a	a	DET
ajst-32396	21	3	dataset	dataset	NOUN
ajst-32396	21	4	of	of	ADP
ajst-32396	21	5	given	give	VERB
ajst-32396	21	6	observations	observation	NOUN
ajst-32396	21	7	and	and	CCONJ
ajst-32396	21	8	features	feature	NOUN
ajst-32396	21	9	,	,	PUNCT
ajst-32396	21	10	our	our	PRON
ajst-32396	21	11	goal	goal	NOUN
ajst-32396	21	12	is	be	AUX
ajst-32396	21	13	to	to	PART
ajst-32396	21	14	find	find	VERB
ajst-32396	21	15	a	a	DET
ajst-32396	21	16	lower	lower	ADV
ajst-32396	21	17	-	-	PUNCT
ajst-32396	21	18	dimensional	dimensional	ADJ
ajst-32396	21	19	subspace	subspace	NOUN
ajst-32396	21	20	via	via	ADP
ajst-32396	21	21	an	an	DET
ajst-32396	21	22	orthogonal	orthogonal	ADJ
ajst-32396	21	23	transformation	transformation	NOUN
ajst-32396	21	24	of	of	ADP
ajst-32396	21	25	the	the	DET
ajst-32396	21	26	data	datum	NOUN
ajst-32396	21	27	matrix	matrix	NOUN
ajst-32396	21	28	that	that	PRON
ajst-32396	21	29	maximizes	maximize	VERB
ajst-32396	21	30	the	the	DET
ajst-32396	21	31	preserved	preserve	VERB
ajst-32396	21	32	variance	variance	NOUN
ajst-32396	21	33	.	.	PUNCT
ajst-32396	22	1	the	the	DET
ajst-32396	22	2	relationships	relationship	NOUN
ajst-32396	22	3	between	between	ADP
ajst-32396	22	4	the	the	DET
ajst-32396	22	5	features	feature	NOUN
ajst-32396	22	6	are	be	AUX
ajst-32396	22	7	assumed	assume	VERB
ajst-32396	22	8	to	to	PART
ajst-32396	22	9	be	be	AUX
ajst-32396	22	10	linear	linear	ADJ
ajst-32396	22	11	,	,	PUNCT
ajst-32396	23	1	where	where	SCONJ
ajst-32396	23	2	directions	direction	NOUN
ajst-32396	23	3	with	with	ADP
ajst-32396	23	4	largest	large	ADJ
ajst-32396	23	5	variance	variance	NOUN
ajst-32396	23	6	capturing	capture	VERB
ajst-32396	23	7	the	the	DET
ajst-32396	23	8	most	most	ADJ
ajst-32396	23	9	structure	structure	NOUN
ajst-32396	23	10	[	[	X
ajst-32396	23	11	4	4	NUM
ajst-32396	23	12	]	]	PUNCT
ajst-32396	23	13	.	.	PUNCT
ajst-32396	24	1	225	225	NUM
ajst-32396	24	2	before	before	ADP
ajst-32396	24	3	constructing	construct	VERB
ajst-32396	24	4	the	the	DET
ajst-32396	24	5	covariance	covariance	NOUN
ajst-32396	24	6	matrix	matrix	NOUN
ajst-32396	24	7	,	,	PUNCT
ajst-32396	24	8	the	the	DET
ajst-32396	24	9	idea	idea	NOUN
ajst-32396	24	10	of	of	ADP
ajst-32396	24	11	centering	center	VERB
ajst-32396	24	12	with	with	ADP
ajst-32396	24	13	mean	mean	ADJ
ajst-32396	24	14	value	value	NOUN
ajst-32396	24	15	is	be	AUX
ajst-32396	24	16	required	require	VERB
ajst-32396	24	17	to	to	PART
ajst-32396	24	18	be	be	AUX
ajst-32396	24	19	executed	execute	VERB
ajst-32396	24	20	to	to	PART
ajst-32396	24	21	eliminate	eliminate	VERB
ajst-32396	24	22	the	the	DET
ajst-32396	24	23	bias	bias	NOUN
ajst-32396	24	24	toward	toward	ADP
ajst-32396	24	25	origin	origin	NOUN
ajst-32396	24	26	.	.	PUNCT
ajst-32396	25	1	after	after	ADP
ajst-32396	25	2	computing	compute	VERB
ajst-32396	25	3	the	the	DET
ajst-32396	25	4	covariance	covariance	NOUN
ajst-32396	25	5	matrix	matrix	NOUN
ajst-32396	25	6	,	,	PUNCT
ajst-32396	25	7	according	accord	VERB
ajst-32396	25	8	to	to	ADP
ajst-32396	25	9	the	the	DET
ajst-32396	25	10	lagrange	lagrange	NOUN
ajst-32396	25	11	multipliers	multiplier	NOUN
ajst-32396	25	12	,	,	PUNCT
ajst-32396	25	13	under	under	ADP
ajst-32396	25	14	the	the	DET
ajst-32396	25	15	constraints	constraint	NOUN
ajst-32396	25	16	of	of	ADP
ajst-32396	25	17	unit	unit	NOUN
ajst-32396	25	18	vector	vector	NOUN
ajst-32396	25	19	,	,	PUNCT
ajst-32396	25	20	we	we	PRON
ajst-32396	25	21	could	could	AUX
ajst-32396	25	22	take	take	VERB
ajst-32396	25	23	partial	partial	ADJ
ajst-32396	25	24	derivative	derivative	NOUN
ajst-32396	25	25	to	to	ADP
ajst-32396	25	26	the	the	DET
ajst-32396	25	27	lagrangian	lagrangian	NOUN
ajst-32396	25	28	that	that	PRON
ajst-32396	25	29	could	could	AUX
ajst-32396	25	30	be	be	AUX
ajst-32396	25	31	simplified	simplify	VERB
ajst-32396	25	32	into	into	ADP
ajst-32396	25	33	an	an	DET
ajst-32396	25	34	eigenvalue	eigenvalue	ADJ
ajst-32396	25	35	equation	equation	NOUN
ajst-32396	25	36	.	.	PUNCT
ajst-32396	26	1	this	this	DET
ajst-32396	26	2	method	method	NOUN
ajst-32396	26	3	efficiently	efficiently	ADV
ajst-32396	26	4	converts	convert	VERB
ajst-32396	26	5	pca	pca	PROPN
ajst-32396	26	6	into	into	ADP
ajst-32396	26	7	an	an	DET
ajst-32396	26	8	eigenvalue	eigenvalue	NOUN
ajst-32396	26	9	problem	problem	NOUN
ajst-32396	26	10	,	,	PUNCT
ajst-32396	26	11	indicating	indicate	VERB
ajst-32396	26	12	that	that	SCONJ
ajst-32396	26	13	the	the	DET
ajst-32396	26	14	principal	principal	ADJ
ajst-32396	26	15	components	component	NOUN
ajst-32396	26	16	are	be	AUX
ajst-32396	26	17	eigenvectors	eigenvector	NOUN
ajst-32396	26	18	of	of	ADP
ajst-32396	26	19	the	the	DET
ajst-32396	26	20	covariance	covariance	NOUN
ajst-32396	26	21	matrix	matrix	NOUN
ajst-32396	26	22	.	.	PUNCT
ajst-32396	27	1	singular	singular	PROPN
ajst-32396	27	2	value	value	NOUN
ajst-32396	27	3	decomposition	decomposition	NOUN
ajst-32396	27	4	,	,	PUNCT
ajst-32396	27	5	outputting	output	VERB
ajst-32396	27	6	orthogonal	orthogonal	ADJ
ajst-32396	27	7	matrices	matrix	NOUN
ajst-32396	27	8	,	,	PUNCT
ajst-32396	27	9	performs	perform	VERB
ajst-32396	27	10	among	among	ADP
ajst-32396	27	11	data	datum	NOUN
ajst-32396	27	12	centering	center	VERB
ajst-32396	27	13	in	in	ADP
ajst-32396	27	14	pca	pca	PROPN
ajst-32396	27	15	method	method	NOUN
ajst-32396	27	16	.	.	PUNCT
ajst-32396	28	1	the	the	DET
ajst-32396	28	2	svd	svd	PROPN
ajst-32396	28	3	method	method	VERB
ajst-32396	28	4	directly	directly	ADV
ajst-32396	28	5	decomposes	decompose	VERB
ajst-32396	28	6	the	the	DET
ajst-32396	28	7	matrix	matrix	NOUN
ajst-32396	28	8	which	which	PRON
ajst-32396	28	9	avoids	avoid	VERB
ajst-32396	28	10	redundant	redundant	ADJ
ajst-32396	28	11	covariance	covariance	NOUN
ajst-32396	28	12	calculations	calculation	NOUN
ajst-32396	28	13	.	.	PUNCT
ajst-32396	29	1	in	in	ADP
ajst-32396	29	2	summary	summary	NOUN
ajst-32396	29	3	,	,	PUNCT
ajst-32396	29	4	pca	pca	PROPN
ajst-32396	29	5	is	be	AUX
ajst-32396	29	6	a	a	DET
ajst-32396	29	7	special	special	ADJ
ajst-32396	29	8	application	application	NOUN
ajst-32396	29	9	of	of	ADP
ajst-32396	29	10	svd	svd	PROPN
ajst-32396	29	11	on	on	ADP
ajst-32396	29	12	centered	center	VERB
ajst-32396	29	13	data	datum	NOUN
ajst-32396	29	14	[	[	X
ajst-32396	29	15	5	5	NUM
ajst-32396	29	16	]	]	PUNCT
ajst-32396	29	17	.	.	PUNCT
ajst-32396	30	1	3	3	X
ajst-32396	30	2	.	.	X
ajst-32396	30	3	different	different	ADJ
ajst-32396	30	4	types	type	NOUN
ajst-32396	30	5	of	of	ADP
ajst-32396	30	6	pca	pca	PROPN
ajst-32396	30	7	method	method	NOUN
ajst-32396	30	8	3.1	3.1	NUM
ajst-32396	30	9	kernel	kernel	NOUN
ajst-32396	30	10	pca	pca	PROPN
ajst-32396	30	11	the	the	DET
ajst-32396	30	12	motivation	motivation	NOUN
ajst-32396	30	13	of	of	ADP
ajst-32396	30	14	kernel	kernel	PROPN
ajst-32396	30	15	pca	pca	PROPN
ajst-32396	30	16	is	be	AUX
ajst-32396	30	17	to	to	PART
ajst-32396	30	18	consider	consider	VERB
ajst-32396	30	19	linearity	linearity	NOUN
ajst-32396	30	20	since	since	SCONJ
ajst-32396	30	21	the	the	DET
ajst-32396	30	22	kernel	kernel	PROPN
ajst-32396	30	23	methods	method	NOUN
ajst-32396	30	24	are	be	AUX
ajst-32396	30	25	a	a	DET
ajst-32396	30	26	class	class	NOUN
ajst-32396	30	27	of	of	ADP
ajst-32396	30	28	widely	widely	ADV
ajst-32396	30	29	-	-	PUNCT
ajst-32396	30	30	used	use	VERB
ajst-32396	30	31	machine	machine	NOUN
ajst-32396	30	32	learning	learn	VERB
ajst-32396	30	33	techniques	technique	NOUN
ajst-32396	30	34	that	that	PRON
ajst-32396	30	35	enable	enable	VERB
ajst-32396	30	36	linear	linear	NOUN
ajst-32396	30	37	models	model	NOUN
ajst-32396	30	38	—	—	PUNCT
ajst-32396	30	39	such	such	ADJ
ajst-32396	30	40	as	as	ADP
ajst-32396	30	41	regression	regression	NOUN
ajst-32396	30	42	,	,	PUNCT
ajst-32396	30	43	svms	svms	NOUN
ajst-32396	30	44	,	,	PUNCT
ajst-32396	30	45	pca	pca	PROPN
ajst-32396	30	46	,	,	PUNCT
ajst-32396	30	47	and	and	CCONJ
ajst-32396	30	48	lda	lda	PROPN
ajst-32396	30	49	—	—	PUNCT
ajst-32396	30	50	to	to	PART
ajst-32396	30	51	learn	learn	VERB
ajst-32396	30	52	and	and	CCONJ
ajst-32396	30	53	represent	represent	VERB
ajst-32396	30	54	complex	complex	ADJ
ajst-32396	30	55	nonlinear	nonlinear	ADJ
ajst-32396	30	56	patterns	pattern	NOUN
ajst-32396	30	57	[	[	X
ajst-32396	30	58	6	6	NUM
ajst-32396	30	59	]	]	PUNCT
ajst-32396	30	60	.	.	PUNCT
ajst-32396	31	1	linear	linear	PROPN
ajst-32396	31	2	pca	pca	PROPN
ajst-32396	31	3	may	may	AUX
ajst-32396	31	4	fail	fail	VERB
ajst-32396	31	5	when	when	SCONJ
ajst-32396	31	6	data	datum	NOUN
ajst-32396	31	7	lies	lie	VERB
ajst-32396	31	8	on	on	ADP
ajst-32396	31	9	nonlinear	nonlinear	ADJ
ajst-32396	31	10	manifolds	manifold	NOUN
ajst-32396	31	11	.	.	PUNCT
ajst-32396	32	1	it	it	PRON
ajst-32396	32	2	maps	map	VERB
ajst-32396	32	3	the	the	DET
ajst-32396	32	4	data	datum	NOUN
ajst-32396	32	5	from	from	ADP
ajst-32396	32	6	high	high	ADJ
ajst-32396	32	7	-	-	PUNCT
ajst-32396	32	8	dimensional	dimensional	ADJ
ajst-32396	32	9	space	space	NOUN
ajst-32396	32	10	which	which	PRON
ajst-32396	32	11	is	be	AUX
ajst-32396	32	12	nonlinear	nonlinear	ADJ
ajst-32396	32	13	to	to	PART
ajst-32396	32	14	become	become	VERB
ajst-32396	32	15	linearly	linearly	ADV
ajst-32396	32	16	separable	separable	ADJ
ajst-32396	32	17	[	[	X
ajst-32396	32	18	7	7	NUM
ajst-32396	32	19	]	]	PUNCT
ajst-32396	32	20	.	.	PUNCT
ajst-32396	33	1	the	the	DET
ajst-32396	33	2	core	core	NOUN
ajst-32396	33	3	idea	idea	NOUN
ajst-32396	33	4	is	be	AUX
ajst-32396	33	5	to	to	PART
ajst-32396	33	6	implement	implement	VERB
ajst-32396	33	7	kernel	kernel	PROPN
ajst-32396	33	8	function	function	NOUN
ajst-32396	33	9	to	to	PART
ajst-32396	33	10	compute	compute	VERB
ajst-32396	33	11	the	the	DET
ajst-32396	33	12	inner	inner	ADJ
ajst-32396	33	13	products	product	NOUN
ajst-32396	33	14	by	by	ADP
ajst-32396	33	15	mapping	map	VERB
ajst-32396	33	16	the	the	DET
ajst-32396	33	17	data	datum	NOUN
ajst-32396	33	18	to	to	PART
ajst-32396	33	19	feature	feature	VERB
ajst-32396	33	20	space	space	NOUN
ajst-32396	33	21	.	.	PUNCT
ajst-32396	34	1	for	for	ADP
ajst-32396	34	2	kernels	kernel	NOUN
ajst-32396	34	3	that	that	PRON
ajst-32396	34	4	depend	depend	VERB
ajst-32396	34	5	on	on	ADP
ajst-32396	34	6	only	only	ADJ
ajst-32396	34	7	dot	dot	NOUN
ajst-32396	34	8	products	product	NOUN
ajst-32396	34	9	or	or	CCONJ
ajst-32396	34	10	distance	distance	NOUN
ajst-32396	34	11	in	in	ADP
ajst-32396	34	12	input	input	NOUN
ajst-32396	34	13	space	space	NOUN
ajst-32396	34	14	,	,	PUNCT
ajst-32396	34	15	kpca	kpca	PROPN
ajst-32396	34	16	’s	’s	PART
ajst-32396	34	17	unitary	unitary	ADJ
ajst-32396	34	18	invariance	invariance	NOUN
ajst-32396	34	19	derives	derive	VERB
ajst-32396	34	20	from	from	ADP
ajst-32396	34	21	the	the	DET
ajst-32396	34	22	sole	sole	ADJ
ajst-32396	34	23	dependence	dependence	NOUN
ajst-32396	34	24	of	of	ADP
ajst-32396	34	25	its	its	PRON
ajst-32396	34	26	algorithm	algorithm	NOUN
ajst-32396	34	27	on	on	ADP
ajst-32396	34	28	the	the	DET
ajst-32396	34	29	kernel	kernel	PROPN
ajst-32396	34	30	matrix	matrix	NOUN
ajst-32396	34	31	's	's	PART
ajst-32396	34	32	values	value	NOUN
ajst-32396	34	33	[	[	X
ajst-32396	34	34	2	2	NUM
ajst-32396	34	35	]	]	PUNCT
ajst-32396	34	36	.	.	PUNCT
ajst-32396	35	1	kpca	kpca	PROPN
ajst-32396	35	2	works	work	VERB
ajst-32396	35	3	even	even	ADV
ajst-32396	35	4	if	if	SCONJ
ajst-32396	35	5	the	the	DET
ajst-32396	35	6	feature	feature	NOUN
ajst-32396	35	7	space	space	NOUN
ajst-32396	35	8	is	be	AUX
ajst-32396	35	9	of	of	ADP
ajst-32396	35	10	infinite	infinite	ADJ
ajst-32396	35	11	dimension	dimension	NOUN
ajst-32396	35	12	since	since	SCONJ
ajst-32396	35	13	the	the	DET
ajst-32396	35	14	computations	computation	NOUN
ajst-32396	35	15	merely	merely	ADV
ajst-32396	35	16	rely	rely	VERB
ajst-32396	35	17	on	on	ADP
ajst-32396	35	18	the	the	DET
ajst-32396	35	19	inner	inner	ADJ
ajst-32396	35	20	products	product	NOUN
ajst-32396	35	21	[	[	X
ajst-32396	35	22	8	8	NUM
ajst-32396	35	23	]	]	PUNCT
ajst-32396	35	24	.	.	PUNCT
ajst-32396	36	1	necessarily	necessarily	ADV
ajst-32396	36	2	,	,	PUNCT
ajst-32396	36	3	multiple	multiple	ADJ
ajst-32396	36	4	kpca	kpca	NOUN
ajst-32396	36	5	could	could	AUX
ajst-32396	36	6	be	be	AUX
ajst-32396	36	7	applied	apply	VERB
ajst-32396	36	8	under	under	ADP
ajst-32396	36	9	high	high	ADJ
ajst-32396	36	10	-	-	PUNCT
ajst-32396	36	11	dimensional	dimensional	ADJ
ajst-32396	36	12	space	space	NOUN
ajst-32396	36	13	as	as	ADV
ajst-32396	36	14	well	well	ADV
ajst-32396	36	15	,	,	PUNCT
ajst-32396	36	16	where	where	SCONJ
ajst-32396	36	17	we	we	PRON
ajst-32396	36	18	could	could	AUX
ajst-32396	36	19	find	find	VERB
ajst-32396	36	20	an	an	DET
ajst-32396	36	21	actual	actual	ADJ
ajst-32396	36	22	example	example	NOUN
ajst-32396	36	23	in	in	ADP
ajst-32396	36	24	image	image	NOUN
ajst-32396	36	25	features	feature	VERB
ajst-32396	36	26	reduction	reduction	NOUN
ajst-32396	37	1	[	[	X
ajst-32396	37	2	9	9	NUM
ajst-32396	37	3	]	]	PUNCT
ajst-32396	37	4	.	.	PUNCT
ajst-32396	38	1	kpca	kpca	PROPN
ajst-32396	38	2	also	also	ADV
ajst-32396	38	3	plays	play	VERB
ajst-32396	38	4	a	a	DET
ajst-32396	38	5	significant	significant	ADJ
ajst-32396	38	6	role	role	NOUN
ajst-32396	38	7	in	in	ADP
ajst-32396	38	8	deep	deep	ADJ
ajst-32396	38	9	learning	learning	NOUN
ajst-32396	38	10	since	since	SCONJ
ajst-32396	38	11	it	it	PRON
ajst-32396	38	12	retains	retain	VERB
ajst-32396	38	13	following	follow	VERB
ajst-32396	38	14	advantages	advantage	NOUN
ajst-32396	38	15	:	:	PUNCT
ajst-32396	38	16	solutions	solution	NOUN
ajst-32396	38	17	are	be	AUX
ajst-32396	38	18	from	from	ADP
ajst-32396	38	19	linear	linear	ADJ
ajst-32396	38	20	algebra	algebra	NOUN
ajst-32396	38	21	that	that	PRON
ajst-32396	38	22	guarantees	guarantee	VERB
ajst-32396	38	23	transparency	transparency	NOUN
ajst-32396	38	24	,	,	PUNCT
ajst-32396	38	25	high	high	ADJ
ajst-32396	38	26	efficiency	efficiency	NOUN
ajst-32396	38	27	for	for	ADP
ajst-32396	38	28	medium	medium	ADJ
ajst-32396	38	29	datasets	dataset	NOUN
ajst-32396	38	30	as	as	ADV
ajst-32396	38	31	well	well	ADV
ajst-32396	38	32	as	as	ADP
ajst-32396	38	33	the	the	DET
ajst-32396	38	34	customized	customize	VERB
ajst-32396	38	35	kernels	kernel	NOUN
ajst-32396	38	36	which	which	PRON
ajst-32396	38	37	ensure	ensure	VERB
ajst-32396	38	38	the	the	DET
ajst-32396	38	39	portability	portability	NOUN
ajst-32396	38	40	.	.	PUNCT
ajst-32396	39	1	for	for	ADP
ajst-32396	39	2	instance	instance	NOUN
ajst-32396	39	3	,	,	PUNCT
ajst-32396	39	4	facial	facial	ADJ
ajst-32396	39	5	recognition	recognition	NOUN
ajst-32396	39	6	would	would	AUX
ajst-32396	39	7	be	be	AUX
ajst-32396	39	8	a	a	DET
ajst-32396	39	9	great	great	ADJ
ajst-32396	39	10	example	example	NOUN
ajst-32396	39	11	applying	apply	VERB
ajst-32396	39	12	kernel	kernel	PROPN
ajst-32396	39	13	pca	pca	PROPN
ajst-32396	39	14	since	since	SCONJ
ajst-32396	39	15	variations	variation	NOUN
ajst-32396	39	16	likes	like	VERB
ajst-32396	39	17	a	a	DET
ajst-32396	39	18	smile	smile	NOUN
ajst-32396	39	19	in	in	ADP
ajst-32396	39	20	expressions	expression	NOUN
ajst-32396	39	21	are	be	AUX
ajst-32396	39	22	extremely	extremely	ADV
ajst-32396	39	23	non	non	ADJ
ajst-32396	39	24	-	-	ADJ
ajst-32396	39	25	linear	linear	ADJ
ajst-32396	39	26	[	[	X
ajst-32396	39	27	10	10	NUM
ajst-32396	39	28	]	]	PUNCT
ajst-32396	39	29	,	,	PUNCT
ajst-32396	39	30	where	where	SCONJ
ajst-32396	39	31	we	we	PRON
ajst-32396	39	32	could	could	AUX
ajst-32396	39	33	find	find	VERB
ajst-32396	39	34	a	a	DET
ajst-32396	39	35	solution	solution	NOUN
ajst-32396	39	36	among	among	ADP
ajst-32396	39	37	wang	wang	PROPN
ajst-32396	39	38	&	&	CCONJ
ajst-32396	39	39	zhang	zhang	PROPN
ajst-32396	39	40	’s	’s	PART
ajst-32396	39	41	research	research	NOUN
ajst-32396	39	42	(	(	PUNCT
ajst-32396	39	43	2010	2010	NUM
ajst-32396	39	44	)	)	PUNCT
ajst-32396	39	45	that	that	PRON
ajst-32396	39	46	stated	state	VERB
ajst-32396	39	47	the	the	DET
ajst-32396	39	48	experimental	experimental	ADJ
ajst-32396	39	49	results	result	NOUN
ajst-32396	39	50	of	of	ADP
ajst-32396	39	51	kpca	kpca	PROPN
ajst-32396	39	52	outperforms	outperform	VERB
ajst-32396	39	53	conventional	conventional	ADJ
ajst-32396	39	54	pca	pca	NOUN
ajst-32396	39	55	both	both	PRON
ajst-32396	39	56	in	in	ADP
ajst-32396	39	57	dimensionality	dimensionality	NOUN
ajst-32396	39	58	reduction	reduction	NOUN
ajst-32396	39	59	and	and	CCONJ
ajst-32396	39	60	overall	overall	ADJ
ajst-32396	39	61	performance	performance	NOUN
ajst-32396	39	62	,	,	PUNCT
ajst-32396	39	63	achieving	achieve	VERB
ajst-32396	39	64	up	up	ADP
ajst-32396	39	65	to	to	PART
ajst-32396	39	66	90	90	NUM
ajst-32396	39	67	%	%	NOUN
ajst-32396	39	68	accuracy	accuracy	NOUN
ajst-32396	39	69	in	in	ADP
ajst-32396	39	70	their	their	PRON
ajst-32396	39	71	experiments	experiment	NOUN
ajst-32396	39	72	[	[	X
ajst-32396	39	73	11	11	NUM
ajst-32396	39	74	]	]	PUNCT
ajst-32396	39	75	.	.	PUNCT
ajst-32396	40	1	3.2	3.2	NUM
ajst-32396	40	2	sparse	sparse	ADJ
ajst-32396	40	3	pca	pca	PROPN
ajst-32396	40	4	when	when	SCONJ
ajst-32396	40	5	analyzing	analyze	VERB
ajst-32396	40	6	datasets	dataset	NOUN
ajst-32396	40	7	with	with	ADP
ajst-32396	40	8	thousands	thousand	NOUN
ajst-32396	40	9	of	of	ADP
ajst-32396	40	10	features	feature	NOUN
ajst-32396	40	11	,	,	PUNCT
ajst-32396	40	12	standard	standard	ADJ
ajst-32396	40	13	pca	pca	NOUN
ajst-32396	40	14	produces	produce	VERB
ajst-32396	40	15	dense	dense	ADJ
ajst-32396	40	16	loadings	loading	NOUN
ajst-32396	40	17	because	because	SCONJ
ajst-32396	40	18	every	every	DET
ajst-32396	40	19	feature	feature	NOUN
ajst-32396	40	20	may	may	AUX
ajst-32396	40	21	occupy	occupy	VERB
ajst-32396	40	22	a	a	DET
ajst-32396	40	23	weight	weight	NOUN
ajst-32396	40	24	in	in	ADP
ajst-32396	40	25	each	each	DET
ajst-32396	40	26	component	component	NOUN
ajst-32396	40	27	.	.	PUNCT
ajst-32396	41	1	the	the	DET
ajst-32396	41	2	sparse	sparse	ADJ
ajst-32396	41	3	pca	pca	PROPN
ajst-32396	41	4	,	,	PUNCT
ajst-32396	41	5	integrating	integrate	VERB
ajst-32396	41	6	the	the	DET
ajst-32396	41	7	sparse	sparse	ADJ
ajst-32396	41	8	constraints	constraint	NOUN
ajst-32396	41	9	into	into	ADP
ajst-32396	41	10	the	the	DET
ajst-32396	41	11	optimization	optimization	NOUN
ajst-32396	41	12	process	process	NOUN
ajst-32396	41	13	,	,	PUNCT
ajst-32396	41	14	could	could	AUX
ajst-32396	41	15	continue	continue	VERB
ajst-32396	41	16	in	in	ADP
ajst-32396	41	17	finding	find	VERB
ajst-32396	41	18	out	out	ADP
ajst-32396	41	19	the	the	DET
ajst-32396	41	20	maximum	maximum	ADJ
ajst-32396	41	21	variance	variance	NOUN
ajst-32396	41	22	.	.	PUNCT
ajst-32396	42	1	the	the	DET
ajst-32396	42	2	lasso	lasso	NOUN
ajst-32396	42	3	method	method	NOUN
ajst-32396	42	4	applies	apply	VERB
ajst-32396	42	5	an	an	DET
ajst-32396	42	6	l1	l1	PROPN
ajst-32396	42	7	penalty	penalty	NOUN
ajst-32396	42	8	(	(	PUNCT
ajst-32396	42	9	a	a	DET
ajst-32396	42	10	bound	bind	VERB
ajst-32396	42	11	on	on	ADP
ajst-32396	42	12	the	the	DET
ajst-32396	42	13	sum	sum	NOUN
ajst-32396	42	14	of	of	ADP
ajst-32396	42	15	the	the	DET
ajst-32396	42	16	absolute	absolute	ADJ
ajst-32396	42	17	coefficient	coefficient	NOUN
ajst-32396	42	18	values	value	NOUN
ajst-32396	42	19	)	)	PUNCT
ajst-32396	42	20	to	to	ADP
ajst-32396	42	21	the	the	DET
ajst-32396	42	22	regression	regression	NOUN
ajst-32396	42	23	model	model	NOUN
ajst-32396	42	24	,	,	PUNCT
ajst-32396	42	25	resulting	result	VERB
ajst-32396	42	26	in	in	ADP
ajst-32396	42	27	a	a	DET
ajst-32396	42	28	sparse	sparse	ADJ
ajst-32396	42	29	solution	solution	NOUN
ajst-32396	42	30	where	where	SCONJ
ajst-32396	42	31	some	some	DET
ajst-32396	42	32	coefficients	coefficient	NOUN
ajst-32396	42	33	are	be	AUX
ajst-32396	42	34	driven	drive	VERB
ajst-32396	42	35	to	to	ADP
ajst-32396	42	36	zero	zero	NUM
ajst-32396	42	37	[	[	X
ajst-32396	42	38	4	4	NUM
ajst-32396	42	39	]	]	PUNCT
ajst-32396	42	40	,	,	PUNCT
ajst-32396	42	41	could	could	AUX
ajst-32396	42	42	continuously	continuously	ADV
ajst-32396	42	43	shrink	shrink	VERB
ajst-32396	42	44	the	the	DET
ajst-32396	42	45	coefficients	coefficient	NOUN
ajst-32396	42	46	toward	toward	ADP
ajst-32396	42	47	zero	zero	NUM
ajst-32396	42	48	,	,	PUNCT
ajst-32396	42	49	thus	thus	ADV
ajst-32396	42	50	gaining	gain	VERB
ajst-32396	42	51	its	its	PRON
ajst-32396	42	52	prediction	prediction	NOUN
ajst-32396	42	53	accuracy	accuracy	NOUN
ajst-32396	42	54	via	via	ADP
ajst-32396	42	55	the	the	DET
ajst-32396	42	56	bias	bias	NOUN
ajst-32396	42	57	variance	variance	NOUN
ajst-32396	42	58	trade	trade	NOUN
ajst-32396	42	59	-	-	PUNCT
ajst-32396	42	60	off	off	NOUN
ajst-32396	42	61	could	could	AUX
ajst-32396	42	62	produce	produce	VERB
ajst-32396	42	63	a	a	DET
ajst-32396	42	64	sparse	sparse	ADJ
ajst-32396	42	65	model	model	NOUN
ajst-32396	42	66	.	.	PUNCT
ajst-32396	43	1	this	this	PRON
ajst-32396	43	2	is	be	AUX
ajst-32396	43	3	achieved	achieve	VERB
ajst-32396	43	4	by	by	ADP
ajst-32396	43	5	using	use	VERB
ajst-32396	43	6	an	an	DET
ajst-32396	43	7	l1	l1	NOUN
ajst-32396	43	8	-	-	PUNCT
ajst-32396	43	9	norm	norm	NOUN
ajst-32396	43	10	(	(	PUNCT
ajst-32396	43	11	lasso	lasso	NOUN
ajst-32396	43	12	)	)	PUNCT
ajst-32396	43	13	penalty	penalty	NOUN
ajst-32396	43	14	.	.	PUNCT
ajst-32396	44	1	to	to	PART
ajst-32396	44	2	implement	implement	VERB
ajst-32396	44	3	spca	spca	PROPN
ajst-32396	44	4	,	,	PUNCT
ajst-32396	44	5	we	we	PRON
ajst-32396	44	6	directly	directly	ADV
ajst-32396	44	7	incorporate	incorporate	VERB
ajst-32396	44	8	l1	l1	PROPN
ajst-32396	44	9	penalties	penalty	NOUN
ajst-32396	44	10	into	into	ADP
ajst-32396	44	11	the	the	DET
ajst-32396	44	12	singular	singular	ADJ
ajst-32396	44	13	value	value	NOUN
ajst-32396	44	14	decomposition	decomposition	NOUN
ajst-32396	44	15	(	(	PUNCT
ajst-32396	44	16	svd	svd	PROPN
ajst-32396	44	17	)	)	PUNCT
ajst-32396	44	18	form	form	VERB
ajst-32396	44	19	underlying	underlie	VERB
ajst-32396	44	20	pca	pca	NOUN
ajst-32396	44	21	or	or	CCONJ
ajst-32396	44	22	reconstruct	reconstruct	VERB
ajst-32396	44	23	it	it	PRON
ajst-32396	44	24	in	in	ADP
ajst-32396	44	25	a	a	DET
ajst-32396	44	26	regression	regression	NOUN
ajst-32396	44	27	form	form	NOUN
ajst-32396	44	28	[	[	X
ajst-32396	44	29	3	3	NUM
ajst-32396	44	30	]	]	PUNCT
ajst-32396	44	31	.	.	PUNCT
ajst-32396	45	1	spca	spca	PROPN
ajst-32396	45	2	imposes	impose	VERB
ajst-32396	45	3	a	a	DET
ajst-32396	45	4	requirement	requirement	NOUN
ajst-32396	45	5	:	:	PUNCT
ajst-32396	45	6	the	the	DET
ajst-32396	45	7	loadings	loading	NOUN
ajst-32396	45	8	vector	vector	NOUN
ajst-32396	45	9	for	for	ADP
ajst-32396	45	10	each	each	DET
ajst-32396	45	11	principal	principal	ADJ
ajst-32396	45	12	component	component	NOUN
ajst-32396	45	13	should	should	AUX
ajst-32396	45	14	contain	contain	VERB
ajst-32396	45	15	mostly	mostly	ADV
ajst-32396	45	16	zeros	zero	NOUN
ajst-32396	45	17	.	.	PUNCT
ajst-32396	46	1	by	by	ADP
ajst-32396	46	2	setting	set	VERB
ajst-32396	46	3	many	many	ADJ
ajst-32396	46	4	loadings	loading	NOUN
ajst-32396	46	5	to	to	ADP
ajst-32396	46	6	zero	zero	NUM
ajst-32396	46	7	,	,	PUNCT
ajst-32396	46	8	spca	spca	PROPN
ajst-32396	46	9	automatically	automatically	ADV
ajst-32396	46	10	identifies	identify	VERB
ajst-32396	46	11	a	a	DET
ajst-32396	46	12	small	small	ADJ
ajst-32396	46	13	subset	subset	NOUN
ajst-32396	46	14	of	of	ADP
ajst-32396	46	15	relevant	relevant	ADJ
ajst-32396	46	16	features	feature	NOUN
ajst-32396	46	17	associated	associate	VERB
ajst-32396	46	18	with	with	ADP
ajst-32396	46	19	each	each	DET
ajst-32396	46	20	component	component	NOUN
ajst-32396	46	21	which	which	PRON
ajst-32396	46	22	transforms	transform	VERB
ajst-32396	46	23	the	the	DET
ajst-32396	46	24	component	component	NOUN
ajst-32396	46	25	from	from	ADP
ajst-32396	46	26	an	an	DET
ajst-32396	46	27	abstract	abstract	ADJ
ajst-32396	46	28	combination	combination	NOUN
ajst-32396	46	29	into	into	ADP
ajst-32396	46	30	an	an	DET
ajst-32396	46	31	exact	exact	ADJ
ajst-32396	46	32	pattern	pattern	NOUN
ajst-32396	46	33	.	.	PUNCT
ajst-32396	47	1	its	its	PRON
ajst-32396	47	2	ability	ability	NOUN
ajst-32396	47	3	to	to	PART
ajst-32396	47	4	extract	extract	VERB
ajst-32396	47	5	meaningful	meaningful	ADJ
ajst-32396	47	6	and	and	CCONJ
ajst-32396	47	7	sparse	sparse	ADJ
ajst-32396	47	8	patterns	pattern	NOUN
ajst-32396	47	9	from	from	ADP
ajst-32396	47	10	complex	complex	ADJ
ajst-32396	47	11	datasets	dataset	NOUN
ajst-32396	47	12	has	have	AUX
ajst-32396	47	13	rendered	render	VERB
ajst-32396	47	14	spca	spca	PROPN
ajst-32396	47	15	as	as	ADP
ajst-32396	47	16	an	an	DET
ajst-32396	47	17	essential	essential	ADJ
ajst-32396	47	18	tool	tool	NOUN
ajst-32396	47	19	in	in	ADP
ajst-32396	47	20	data	datum	NOUN
ajst-32396	47	21	analysis	analysis	NOUN
ajst-32396	47	22	.	.	PUNCT
ajst-32396	48	1	among	among	ADP
ajst-32396	48	2	all	all	DET
ajst-32396	48	3	applications	application	NOUN
ajst-32396	48	4	,	,	PUNCT
ajst-32396	48	5	genomics	genomic	NOUN
ajst-32396	48	6	would	would	AUX
ajst-32396	48	7	be	be	AUX
ajst-32396	48	8	the	the	DET
ajst-32396	48	9	most	most	ADV
ajst-32396	48	10	classic	classic	ADJ
ajst-32396	48	11	ones	one	NOUN
ajst-32396	48	12	as	as	SCONJ
ajst-32396	48	13	there	there	PRON
ajst-32396	48	14	are	be	VERB
ajst-32396	48	15	more	more	ADJ
ajst-32396	48	16	features	feature	NOUN
ajst-32396	48	17	than	than	ADP
ajst-32396	48	18	samples	sample	NOUN
ajst-32396	48	19	,	,	PUNCT
ajst-32396	48	20	one	one	NUM
ajst-32396	48	21	of	of	ADP
ajst-32396	48	22	whose	whose	DET
ajst-32396	48	23	solutions	solution	NOUN
ajst-32396	48	24	using	use	VERB
ajst-32396	48	25	spca	spca	PROPN
ajst-32396	48	26	obtains	obtain	VERB
ajst-32396	48	27	higher	high	ADJ
ajst-32396	48	28	accuracy	accuracy	NOUN
ajst-32396	48	29	and	and	CCONJ
ajst-32396	48	30	relevancy	relevancy	NOUN
ajst-32396	48	31	to	to	PART
ajst-32396	48	32	recognize	recognize	VERB
ajst-32396	48	33	the	the	DET
ajst-32396	48	34	genes	gene	NOUN
ajst-32396	48	35	by	by	ADP
ajst-32396	48	36	replacing	replace	VERB
ajst-32396	48	37	the	the	DET
ajst-32396	48	38	elastic	elastic	ADJ
ajst-32396	48	39	net	net	NOUN
ajst-32396	48	40	with	with	ADP
ajst-32396	48	41	l2,1	l2,1	ADJ
ajst-32396	48	42	-	-	PUNCT
ajst-32396	48	43	norm	norm	NOUN
ajst-32396	48	44	penalty	penalty	NOUN
ajst-32396	48	45	,	,	PUNCT
ajst-32396	48	46	which	which	PRON
ajst-32396	48	47	strongly	strongly	ADV
ajst-32396	48	48	supports	support	VERB
ajst-32396	48	49	the	the	DET
ajst-32396	48	50	statement	statement	NOUN
ajst-32396	48	51	[	[	X
ajst-32396	48	52	12	12	NUM
ajst-32396	48	53	]	]	PUNCT
ajst-32396	48	54	.	.	PUNCT
ajst-32396	49	1	226	226	NUM
ajst-32396	49	2	3.3	3.3	NUM
ajst-32396	49	3	robust	robust	ADJ
ajst-32396	49	4	pca	pca	NOUN
ajst-32396	49	5	though	though	SCONJ
ajst-32396	49	6	the	the	DET
ajst-32396	49	7	methods	method	NOUN
ajst-32396	49	8	above	above	ADV
ajst-32396	49	9	are	be	AUX
ajst-32396	49	10	relatively	relatively	ADV
ajst-32396	49	11	comprehensive	comprehensive	ADJ
ajst-32396	49	12	,	,	PUNCT
ajst-32396	49	13	the	the	DET
ajst-32396	49	14	real	real	ADJ
ajst-32396	49	15	-	-	PUNCT
ajst-32396	49	16	world	world	NOUN
ajst-32396	49	17	datasets	dataset	NOUN
ajst-32396	49	18	are	be	AUX
ajst-32396	49	19	usually	usually	ADV
ajst-32396	49	20	contaminated	contaminate	VERB
ajst-32396	49	21	by	by	ADP
ajst-32396	49	22	mess	mess	NOUN
ajst-32396	49	23	such	such	ADJ
ajst-32396	49	24	as	as	ADP
ajst-32396	49	25	corrupted	corrupted	ADJ
ajst-32396	49	26	entries	entry	NOUN
ajst-32396	49	27	and	and	CCONJ
ajst-32396	49	28	missing	missing	ADJ
ajst-32396	49	29	value	value	NOUN
ajst-32396	49	30	.	.	PUNCT
ajst-32396	50	1	under	under	ADP
ajst-32396	50	2	the	the	DET
ajst-32396	50	3	assumption	assumption	NOUN
ajst-32396	50	4	of	of	ADP
ajst-32396	50	5	gaussian	gaussian	ADJ
ajst-32396	50	6	errors	error	NOUN
ajst-32396	50	7	,	,	PUNCT
ajst-32396	50	8	pca	pca	PROPN
ajst-32396	50	9	is	be	AUX
ajst-32396	50	10	proven	prove	VERB
ajst-32396	50	11	to	to	PART
ajst-32396	50	12	be	be	AUX
ajst-32396	50	13	the	the	DET
ajst-32396	50	14	optimal	optimal	ADJ
ajst-32396	50	15	method	method	NOUN
ajst-32396	50	16	for	for	ADP
ajst-32396	50	17	obtaining	obtain	VERB
ajst-32396	50	18	a	a	DET
ajst-32396	50	19	low	low	ADJ
ajst-32396	50	20	-	-	PUNCT
ajst-32396	50	21	rank	rank	NOUN
ajst-32396	50	22	approximation	approximation	NOUN
ajst-32396	50	23	of	of	ADP
ajst-32396	50	24	highdimensional	highdimensional	ADJ
ajst-32396	50	25	data	datum	NOUN
ajst-32396	50	26	in	in	ADP
ajst-32396	50	27	terms	term	NOUN
ajst-32396	50	28	of	of	ADP
ajst-32396	50	29	minimizing	minimize	VERB
ajst-32396	50	30	least	least	ADJ
ajst-32396	50	31	-	-	PUNCT
ajst-32396	50	32	squares	square	NOUN
ajst-32396	50	33	error	error	NOUN
ajst-32396	50	34	[	[	X
ajst-32396	50	35	7	7	NUM
ajst-32396	50	36	]	]	PUNCT
ajst-32396	50	37	,	,	PUNCT
ajst-32396	50	38	the	the	DET
ajst-32396	50	39	robust	robust	ADJ
ajst-32396	50	40	principal	principal	ADJ
ajst-32396	50	41	component	component	NOUN
ajst-32396	50	42	analysis	analysis	NOUN
ajst-32396	50	43	(	(	PUNCT
ajst-32396	50	44	rpca	rpca	NOUN
ajst-32396	50	45	)	)	PUNCT
ajst-32396	50	46	method	method	NOUN
ajst-32396	50	47	reimagines	reimagine	VERB
ajst-32396	50	48	the	the	DET
ajst-32396	50	49	data	datum	NOUN
ajst-32396	50	50	matrix	matrix	NOUN
ajst-32396	50	51	as	as	ADP
ajst-32396	50	52	the	the	DET
ajst-32396	50	53	sum	sum	NOUN
ajst-32396	50	54	of	of	ADP
ajst-32396	50	55	two	two	NUM
ajst-32396	50	56	distinct	distinct	ADJ
ajst-32396	50	57	components	component	NOUN
ajst-32396	50	58	called	call	VERB
ajst-32396	50	59	low	low	ADJ
ajst-32396	50	60	-	-	PUNCT
ajst-32396	50	61	rank	rank	NOUN
ajst-32396	50	62	matrix	matrix	NOUN
ajst-32396	50	63	and	and	CCONJ
ajst-32396	50	64	sparse	sparse	ADJ
ajst-32396	50	65	matrix	matrix	NOUN
ajst-32396	50	66	.	.	PUNCT
ajst-32396	51	1	the	the	DET
ajst-32396	51	2	former	former	ADJ
ajst-32396	51	3	matrix	matrix	NOUN
ajst-32396	51	4	represents	represent	VERB
ajst-32396	51	5	the	the	DET
ajst-32396	51	6	data	datum	NOUN
ajst-32396	51	7	captured	capture	VERB
ajst-32396	51	8	by	by	ADP
ajst-32396	51	9	pca	pca	PROPN
ajst-32396	51	10	under	under	ADP
ajst-32396	51	11	ideal	ideal	ADJ
ajst-32396	51	12	conditions	condition	NOUN
ajst-32396	51	13	and	and	CCONJ
ajst-32396	51	14	the	the	DET
ajst-32396	51	15	latter	latter	ADJ
ajst-32396	51	16	matrix	matrix	NOUN
ajst-32396	51	17	is	be	AUX
ajst-32396	51	18	assumed	assume	VERB
ajst-32396	51	19	to	to	PART
ajst-32396	51	20	be	be	AUX
ajst-32396	51	21	sparse	sparse	ADJ
ajst-32396	51	22	,	,	PUNCT
ajst-32396	51	23	meaning	mean	VERB
ajst-32396	51	24	most	most	ADJ
ajst-32396	51	25	of	of	ADP
ajst-32396	51	26	its	its	PRON
ajst-32396	51	27	entries	entry	NOUN
ajst-32396	51	28	are	be	AUX
ajst-32396	51	29	zero	zero	NUM
ajst-32396	51	30	.	.	PUNCT
ajst-32396	52	1	an	an	DET
ajst-32396	52	2	efficient	efficient	ADJ
ajst-32396	52	3	recovery	recovery	NOUN
ajst-32396	52	4	of	of	ADP
ajst-32396	52	5	most	most	ADJ
ajst-32396	52	6	low	low	ADJ
ajst-32396	52	7	-	-	PUNCT
ajst-32396	52	8	rank	rank	NOUN
ajst-32396	52	9	matrices	matrix	NOUN
ajst-32396	52	10	from	from	ADP
ajst-32396	52	11	most	most	ADJ
ajst-32396	52	12	error	error	NOUN
ajst-32396	52	13	sign	sign	NOUN
ajst-32396	52	14	-	-	PUNCT
ajst-32396	52	15	and	and	CCONJ
ajst-32396	52	16	-	-	PUNCT
ajst-32396	52	17	support	support	NOUN
ajst-32396	52	18	patterns	pattern	NOUN
ajst-32396	52	19	via	via	ADP
ajst-32396	52	20	a	a	DET
ajst-32396	52	21	simple	simple	ADJ
ajst-32396	52	22	convex	convex	NOUN
ajst-32396	52	23	program	program	NOUN
ajst-32396	52	24	was	be	AUX
ajst-32396	52	25	established	establish	VERB
ajst-32396	52	26	by	by	ADP
ajst-32396	52	27	wright	wright	PROPN
ajst-32396	52	28	,	,	PUNCT
ajst-32396	52	29	ganesh	ganesh	PROPN
ajst-32396	52	30	,	,	PUNCT
ajst-32396	52	31	rao	rao	PROPN
ajst-32396	52	32	,	,	PUNCT
ajst-32396	52	33	peng	peng	PROPN
ajst-32396	52	34	,	,	PUNCT
ajst-32396	52	35	and	and	CCONJ
ajst-32396	52	36	ma	ma	PROPN
ajst-32396	53	1	[	[	X
ajst-32396	53	2	5	5	NUM
ajst-32396	53	3	]	]	PUNCT
ajst-32396	53	4	,	,	PUNCT
ajst-32396	53	5	which	which	PRON
ajst-32396	53	6	is	be	AUX
ajst-32396	53	7	also	also	ADV
ajst-32396	53	8	an	an	DET
ajst-32396	53	9	exact	exact	ADJ
ajst-32396	53	10	template	template	NOUN
ajst-32396	53	11	.	.	PUNCT
ajst-32396	54	1	rpca	rpca	PROPN
ajst-32396	54	2	's	's	PART
ajst-32396	54	3	ability	ability	NOUN
ajst-32396	54	4	to	to	PART
ajst-32396	54	5	separate	separate	VERB
ajst-32396	54	6	signal	signal	NOUN
ajst-32396	54	7	from	from	ADP
ajst-32396	54	8	corruption	corruption	NOUN
ajst-32396	54	9	renders	render	VERB
ajst-32396	54	10	its	its	PRON
ajst-32396	54	11	wide	wide	ADJ
ajst-32396	54	12	use	use	NOUN
ajst-32396	54	13	in	in	ADP
ajst-32396	54	14	areas	area	NOUN
ajst-32396	54	15	like	like	ADP
ajst-32396	54	16	face	face	NOUN
ajst-32396	54	17	recognition	recognition	NOUN
ajst-32396	54	18	,	,	PUNCT
ajst-32396	54	19	medical	medical	ADJ
ajst-32396	54	20	imaging	imaging	NOUN
ajst-32396	54	21	and	and	CCONJ
ajst-32396	54	22	financial	financial	ADJ
ajst-32396	54	23	model	model	NOUN
ajst-32396	54	24	etc	etc	X
ajst-32396	54	25	.	.	X
ajst-32396	54	26	yuan	yuan	PROPN
ajst-32396	54	27	,	,	PUNCT
ajst-32396	54	28	xie	xie	PROPN
ajst-32396	54	29	,	,	PUNCT
ajst-32396	54	30	ma	ma	PROPN
ajst-32396	54	31	,	,	PUNCT
ajst-32396	54	32	and	and	CCONJ
ajst-32396	54	33	lam	lam	PROPN
ajst-32396	54	34	(	(	PUNCT
ajst-32396	54	35	2013	2013	NUM
ajst-32396	54	36	)	)	PUNCT
ajst-32396	54	37	suggested	suggest	VERB
ajst-32396	54	38	color	color	NOUN
ajst-32396	54	39	facial	facial	ADJ
ajst-32396	54	40	denoising	denoising	NOUN
ajst-32396	54	41	based	base	VERB
ajst-32396	54	42	on	on	ADP
ajst-32396	54	43	the	the	DET
ajst-32396	54	44	rpca	rpca	NOUN
ajst-32396	54	45	technique	technique	NOUN
ajst-32396	54	46	,	,	PUNCT
ajst-32396	54	47	which	which	PRON
ajst-32396	54	48	indicates	indicate	VERB
ajst-32396	54	49	that	that	SCONJ
ajst-32396	54	50	their	their	PRON
ajst-32396	54	51	approach	approach	NOUN
ajst-32396	54	52	can	can	AUX
ajst-32396	54	53	attain	attain	VERB
ajst-32396	54	54	a	a	DET
ajst-32396	54	55	greater	great	ADJ
ajst-32396	54	56	expectation	expectation	NOUN
ajst-32396	54	57	in	in	ADP
ajst-32396	54	58	terms	term	NOUN
ajst-32396	54	59	of	of	ADP
ajst-32396	54	60	both	both	DET
ajst-32396	54	61	qualitative	qualitative	ADJ
ajst-32396	54	62	evaluation	evaluation	NOUN
ajst-32396	54	63	and	and	CCONJ
ajst-32396	54	64	visual	visual	ADJ
ajst-32396	54	65	quality	quality	NOUN
ajst-32396	54	66	than	than	ADP
ajst-32396	54	67	kpca	kpca	NOUN
ajst-32396	54	68	[	[	X
ajst-32396	54	69	13	13	NUM
ajst-32396	54	70	]	]	PUNCT
ajst-32396	54	71	,	,	PUNCT
ajst-32396	54	72	in	in	ADP
ajst-32396	54	73	contrast	contrast	NOUN
ajst-32396	54	74	to	to	ADP
ajst-32396	54	75	earlier	early	ADJ
ajst-32396	54	76	facial	facial	ADJ
ajst-32396	54	77	recognition	recognition	NOUN
ajst-32396	54	78	using	use	VERB
ajst-32396	54	79	the	the	DET
ajst-32396	54	80	kpca	kpca	PROPN
ajst-32396	54	81	method	method	NOUN
ajst-32396	54	82	.	.	PUNCT
ajst-32396	55	1	where	where	SCONJ
ajst-32396	55	2	classical	classical	ADJ
ajst-32396	55	3	pca	pca	NOUN
ajst-32396	55	4	falls	fall	VERB
ajst-32396	55	5	short	short	ADJ
ajst-32396	55	6	,	,	PUNCT
ajst-32396	55	7	rpca	rpca	NOUN
ajst-32396	55	8	offers	offer	VERB
ajst-32396	55	9	a	a	DET
ajst-32396	55	10	strong	strong	ADJ
ajst-32396	55	11	foundation	foundation	NOUN
ajst-32396	55	12	for	for	ADP
ajst-32396	55	13	high	high	ADJ
ajst-32396	55	14	computing	computing	NOUN
ajst-32396	55	15	needs	need	NOUN
ajst-32396	55	16	.	.	PUNCT
ajst-32396	56	1	an	an	DET
ajst-32396	56	2	approach	approach	NOUN
ajst-32396	56	3	that	that	PRON
ajst-32396	56	4	is	be	AUX
ajst-32396	56	5	not	not	PART
ajst-32396	56	6	overly	overly	ADV
ajst-32396	56	7	sensitive	sensitive	ADJ
ajst-32396	56	8	to	to	ADP
ajst-32396	56	9	any	any	DET
ajst-32396	56	10	one	one	NUM
ajst-32396	56	11	piece	piece	NOUN
ajst-32396	56	12	of	of	ADP
ajst-32396	56	13	data	datum	NOUN
ajst-32396	56	14	is	be	AUX
ajst-32396	56	15	considered	consider	VERB
ajst-32396	56	16	robust	robust	ADJ
ajst-32396	56	17	.	.	PUNCT
ajst-32396	57	1	next	next	ADV
ajst-32396	57	2	,	,	PUNCT
ajst-32396	57	3	the	the	DET
ajst-32396	57	4	concept	concept	NOUN
ajst-32396	57	5	of	of	ADP
ajst-32396	57	6	a	a	DET
ajst-32396	57	7	norm	norm	NOUN
ajst-32396	57	8	of	of	ADP
ajst-32396	57	9	projection	projection	NOUN
ajst-32396	57	10	is	be	AUX
ajst-32396	57	11	presented	present	VERB
ajst-32396	57	12	[	[	PUNCT
ajst-32396	57	13	6	6	NUM
ajst-32396	57	14	]	]	PUNCT
ajst-32396	57	15	.	.	PUNCT
ajst-32396	58	1	wang	wang	PROPN
ajst-32396	58	2	and	and	CCONJ
ajst-32396	58	3	zhu	zhu	PROPN
ajst-32396	58	4	also	also	ADV
ajst-32396	58	5	proposed	propose	VERB
ajst-32396	58	6	that	that	SCONJ
ajst-32396	58	7	pca	pca	PROPN
ajst-32396	58	8	is	be	AUX
ajst-32396	58	9	a	a	DET
ajst-32396	58	10	package	package	NOUN
ajst-32396	58	11	of	of	ADP
ajst-32396	58	12	svd	svd	PROPN
ajst-32396	58	13	.	.	PUNCT
ajst-32396	59	1	in	in	ADP
ajst-32396	59	2	addition	addition	NOUN
ajst-32396	59	3	,	,	PUNCT
ajst-32396	59	4	we	we	PRON
ajst-32396	59	5	can	can	AUX
ajst-32396	59	6	get	get	VERB
ajst-32396	59	7	the	the	DET
ajst-32396	59	8	two	two	NUM
ajst-32396	59	9	directions	direction	NOUN
ajst-32396	59	10	of	of	ADP
ajst-32396	59	11	pca	pca	NOUN
ajst-32396	59	12	by	by	ADP
ajst-32396	59	13	using	use	VERB
ajst-32396	59	14	svd	svd	PROPN
ajst-32396	59	15	,	,	PUNCT
ajst-32396	59	16	if	if	SCONJ
ajst-32396	59	17	we	we	PRON
ajst-32396	59	18	decompose	decompose	VERB
ajst-32396	59	19	the	the	DET
ajst-32396	59	20	eigenvalue	eigenvalue	NOUN
ajst-32396	59	21	of	of	ADP
ajst-32396	59	22	matrix	matrix	NOUN
ajst-32396	59	23	we	we	PRON
ajst-32396	59	24	can	can	AUX
ajst-32396	59	25	only	only	ADV
ajst-32396	59	26	get	get	VERB
ajst-32396	59	27	pca	pca	NOUN
ajst-32396	59	28	with	with	ADP
ajst-32396	59	29	one	one	NUM
ajst-32396	59	30	direction	direction	NOUN
ajst-32396	59	31	[	[	X
ajst-32396	59	32	14	14	NUM
ajst-32396	59	33	]	]	SYM
ajst-32396	59	34	.	.	PUNCT
ajst-32396	60	1	4	4	X
ajst-32396	60	2	.	.	X
ajst-32396	60	3	conclusion	conclusion	NOUN
ajst-32396	60	4	principal	principal	ADJ
ajst-32396	60	5	component	component	NOUN
ajst-32396	60	6	analysis	analysis	NOUN
ajst-32396	60	7	is	be	AUX
ajst-32396	60	8	widely	widely	ADV
ajst-32396	60	9	recognized	recognize	VERB
ajst-32396	60	10	as	as	ADP
ajst-32396	60	11	one	one	NUM
ajst-32396	60	12	of	of	ADP
ajst-32396	60	13	the	the	DET
ajst-32396	60	14	most	most	ADV
ajst-32396	60	15	prominent	prominent	ADJ
ajst-32396	60	16	data	datum	NOUN
ajst-32396	60	17	analysis	analysis	NOUN
ajst-32396	60	18	approaches	approach	NOUN
ajst-32396	60	19	.	.	PUNCT
ajst-32396	61	1	its	its	PRON
ajst-32396	61	2	strength	strength	NOUN
ajst-32396	61	3	comes	come	VERB
ajst-32396	61	4	from	from	ADP
ajst-32396	61	5	a	a	DET
ajst-32396	61	6	straightforward	straightforward	ADJ
ajst-32396	61	7	yet	yet	CCONJ
ajst-32396	61	8	efficient	efficient	ADJ
ajst-32396	61	9	method	method	NOUN
ajst-32396	61	10	:	:	PUNCT
ajst-32396	61	11	breaking	break	VERB
ajst-32396	61	12	down	down	ADP
ajst-32396	61	13	highdimensional	highdimensional	NOUN
ajst-32396	61	14	,	,	PUNCT
ajst-32396	61	15	frequently	frequently	ADV
ajst-32396	61	16	correlated	correlate	VERB
ajst-32396	61	17	variables	variable	NOUN
ajst-32396	61	18	into	into	ADP
ajst-32396	61	19	a	a	DET
ajst-32396	61	20	collection	collection	NOUN
ajst-32396	61	21	of	of	ADP
ajst-32396	61	22	orthogonal	orthogonal	ADJ
ajst-32396	61	23	parts	part	NOUN
ajst-32396	61	24	that	that	PRON
ajst-32396	61	25	represent	represent	VERB
ajst-32396	61	26	the	the	DET
ajst-32396	61	27	directions	direction	NOUN
ajst-32396	61	28	of	of	ADP
ajst-32396	61	29	greatest	great	ADJ
ajst-32396	61	30	variation	variation	NOUN
ajst-32396	61	31	.	.	PUNCT
ajst-32396	62	1	however	however	ADV
ajst-32396	62	2	,	,	PUNCT
ajst-32396	62	3	the	the	DET
ajst-32396	62	4	history	history	NOUN
ajst-32396	62	5	of	of	ADP
ajst-32396	62	6	pca	pca	PROPN
ajst-32396	62	7	demonstrates	demonstrate	VERB
ajst-32396	62	8	both	both	PRON
ajst-32396	62	9	its	its	PRON
ajst-32396	62	10	flexibility	flexibility	NOUN
ajst-32396	62	11	and	and	CCONJ
ajst-32396	62	12	the	the	DET
ajst-32396	62	13	difficulty	difficulty	NOUN
ajst-32396	62	14	in	in	ADP
ajst-32396	62	15	addressing	address	VERB
ajst-32396	62	16	its	its	PRON
ajst-32396	62	17	limits	limit	NOUN
ajst-32396	62	18	in	in	ADP
ajst-32396	62	19	the	the	DET
ajst-32396	62	20	face	face	NOUN
ajst-32396	62	21	of	of	ADP
ajst-32396	62	22	data	datum	NOUN
ajst-32396	62	23	issues	issue	NOUN
ajst-32396	62	24	.	.	PUNCT
ajst-32396	63	1	high	high	ADJ
ajst-32396	63	2	-	-	PUNCT
ajst-32396	63	3	dimensional	dimensional	ADJ
ajst-32396	63	4	datasets	dataset	NOUN
ajst-32396	63	5	are	be	AUX
ajst-32396	63	6	subjected	subject	VERB
ajst-32396	63	7	to	to	PART
ajst-32396	63	8	sparse	sparse	VERB
ajst-32396	63	9	pca	pca	PROPN
ajst-32396	63	10	.	.	PUNCT
ajst-32396	64	1	by	by	ADP
ajst-32396	64	2	enforcing	enforce	VERB
ajst-32396	64	3	sparsity	sparsity	NOUN
ajst-32396	64	4	constraints	constraint	NOUN
ajst-32396	64	5	on	on	ADP
ajst-32396	64	6	component	component	NOUN
ajst-32396	64	7	loadings	loading	NOUN
ajst-32396	64	8	,	,	PUNCT
ajst-32396	64	9	spca	spca	PROPN
ajst-32396	64	10	utilizes	utilize	VERB
ajst-32396	64	11	an	an	DET
ajst-32396	64	12	amount	amount	NOUN
ajst-32396	64	13	of	of	ADP
ajst-32396	64	14	explained	explain	VERB
ajst-32396	64	15	variance	variance	NOUN
ajst-32396	64	16	to	to	PART
ajst-32396	64	17	gain	gain	VERB
ajst-32396	64	18	clarity	clarity	NOUN
ajst-32396	64	19	,	,	PUNCT
ajst-32396	64	20	transforming	transform	VERB
ajst-32396	64	21	abstract	abstract	ADJ
ajst-32396	64	22	principal	principal	ADJ
ajst-32396	64	23	components	component	NOUN
ajst-32396	64	24	into	into	ADP
ajst-32396	64	25	interpretable	interpretable	ADJ
ajst-32396	64	26	factors	factor	NOUN
ajst-32396	64	27	defined	define	VERB
ajst-32396	64	28	by	by	ADP
ajst-32396	64	29	a	a	DET
ajst-32396	64	30	small	small	ADJ
ajst-32396	64	31	subset	subset	NOUN
ajst-32396	64	32	of	of	ADP
ajst-32396	64	33	meaningful	meaningful	ADJ
ajst-32396	64	34	features	feature	NOUN
ajst-32396	64	35	.	.	PUNCT
ajst-32396	65	1	simultaneously	simultaneously	ADV
ajst-32396	65	2	,	,	PUNCT
ajst-32396	65	3	robust	robust	ADJ
ajst-32396	65	4	pca	pca	NOUN
ajst-32396	65	5	emerged	emerge	VERB
ajst-32396	65	6	to	to	PART
ajst-32396	65	7	conquer	conquer	VERB
ajst-32396	65	8	pca	pca	PROPN
ajst-32396	65	9	's	's	PART
ajst-32396	65	10	weakness	weakness	NOUN
ajst-32396	65	11	in	in	ADP
ajst-32396	65	12	handling	handling	NOUN
ajst-32396	65	13	corruptions	corruption	NOUN
ajst-32396	65	14	.	.	PUNCT
ajst-32396	66	1	by	by	ADP
ajst-32396	66	2	decomposing	decompose	VERB
ajst-32396	66	3	data	datum	NOUN
ajst-32396	66	4	into	into	ADP
ajst-32396	66	5	a	a	DET
ajst-32396	66	6	low	low	ADJ
ajst-32396	66	7	-	-	PUNCT
ajst-32396	66	8	rank	rank	NOUN
ajst-32396	66	9	matrix	matrix	NOUN
ajst-32396	66	10	representing	represent	VERB
ajst-32396	66	11	the	the	DET
ajst-32396	66	12	true	true	ADJ
ajst-32396	66	13	underlying	underlie	VERB
ajst-32396	66	14	structure	structure	NOUN
ajst-32396	66	15	and	and	CCONJ
ajst-32396	66	16	a	a	DET
ajst-32396	66	17	sparse	sparse	ADJ
ajst-32396	66	18	matrix	matrix	NOUN
ajst-32396	66	19	capturing	capture	VERB
ajst-32396	66	20	anomalies	anomaly	NOUN
ajst-32396	66	21	,	,	PUNCT
ajst-32396	66	22	rpca	rpca	VERB
ajst-32396	66	23	provides	provide	VERB
ajst-32396	66	24	a	a	DET
ajst-32396	66	25	practical	practical	ADJ
ajst-32396	66	26	framework	framework	NOUN
ajst-32396	66	27	for	for	ADP
ajst-32396	66	28	reliable	reliable	ADJ
ajst-32396	66	29	analysis	analysis	NOUN
ajst-32396	66	30	in	in	ADP
ajst-32396	66	31	noisy	noisy	ADJ
ajst-32396	66	32	,	,	PUNCT
ajst-32396	66	33	realworld	realworld	PROPN
ajst-32396	66	34	environments	environment	NOUN
ajst-32396	66	35	.	.	PUNCT
ajst-32396	67	1	its	its	PRON
ajst-32396	67	2	ability	ability	NOUN
ajst-32396	67	3	to	to	PART
ajst-32396	67	4	identify	identify	VERB
ajst-32396	67	5	and	and	CCONJ
ajst-32396	67	6	avoid	avoid	VERB
ajst-32396	67	7	corruption	corruption	NOUN
ajst-32396	67	8	is	be	AUX
ajst-32396	67	9	undeniably	undeniably	ADV
ajst-32396	67	10	strong	strong	ADJ
ajst-32396	67	11	.	.	PUNCT
ajst-32396	68	1	throughout	throughout	ADP
ajst-32396	68	2	investigation	investigation	NOUN
ajst-32396	68	3	,	,	PUNCT
ajst-32396	68	4	this	this	DET
ajst-32396	68	5	review	review	NOUN
ajst-32396	68	6	serves	serve	VERB
ajst-32396	68	7	as	as	ADP
ajst-32396	68	8	a	a	DET
ajst-32396	68	9	map	map	NOUN
ajst-32396	68	10	for	for	SCONJ
ajst-32396	68	11	the	the	DET
ajst-32396	68	12	researchers	researcher	NOUN
ajst-32396	68	13	tackling	tackle	VERB
ajst-32396	68	14	with	with	ADP
ajst-32396	68	15	increasingly	increasingly	ADV
ajst-32396	68	16	complex	complex	ADJ
ajst-32396	68	17	data	datum	NOUN
ajst-32396	68	18	environments	environment	NOUN
ajst-32396	68	19	.	.	PUNCT
ajst-32396	69	1	in	in	ADP
ajst-32396	69	2	summary	summary	NOUN
ajst-32396	69	3	,	,	PUNCT
ajst-32396	69	4	pca	pca	NOUN
ajst-32396	69	5	remains	remain	VERB
ajst-32396	69	6	as	as	ADV
ajst-32396	69	7	relevant	relevant	ADJ
ajst-32396	69	8	as	as	ADP
ajst-32396	69	9	ever	ever	ADV
ajst-32396	69	10	.	.	PUNCT
ajst-32396	70	1	evolving	evolve	VERB
ajst-32396	70	2	from	from	ADP
ajst-32396	70	3	a	a	DET
ajst-32396	70	4	classical	classical	ADJ
ajst-32396	70	5	method	method	NOUN
ajst-32396	70	6	for	for	ADP
ajst-32396	70	7	reducing	reduce	VERB
ajst-32396	70	8	gaussian	gaussian	ADJ
ajst-32396	70	9	noise	noise	NOUN
ajst-32396	70	10	,	,	PUNCT
ajst-32396	70	11	it	it	PRON
ajst-32396	70	12	now	now	ADV
ajst-32396	70	13	encompasses	encompass	VERB
ajst-32396	70	14	robust	robust	ADJ
ajst-32396	70	15	variants	variant	NOUN
ajst-32396	70	16	such	such	ADJ
ajst-32396	70	17	as	as	ADP
ajst-32396	70	18	spca	spca	PROPN
ajst-32396	70	19	and	and	CCONJ
ajst-32396	70	20	rpca	rpca	PROPN
ajst-32396	70	21	,	,	PUNCT
ajst-32396	70	22	highlighting	highlight	VERB
ajst-32396	70	23	its	its	PRON
ajst-32396	70	24	continued	continued	ADJ
ajst-32396	70	25	importance	importance	NOUN
ajst-32396	70	26	.	.	PUNCT
ajst-32396	71	1	traditional	traditional	ADJ
ajst-32396	71	2	pca	pca	PROPN
ajst-32396	71	3	still	still	ADV
ajst-32396	71	4	serves	serve	VERB
ajst-32396	71	5	as	as	ADP
ajst-32396	71	6	a	a	DET
ajst-32396	71	7	cornerstone	cornerstone	NOUN
ajst-32396	71	8	for	for	ADP
ajst-32396	71	9	analyzing	analyze	VERB
ajst-32396	71	10	standardized	standardized	ADJ
ajst-32396	71	11	datasets	dataset	NOUN
ajst-32396	71	12	,	,	PUNCT
ajst-32396	71	13	while	while	SCONJ
ajst-32396	71	14	spca	spca	PROPN
ajst-32396	71	15	and	and	CCONJ
ajst-32396	71	16	rpca	rpca	PROPN
ajst-32396	71	17	address	address	VERB
ajst-32396	71	18	the	the	DET
ajst-32396	71	19	challenges	challenge	NOUN
ajst-32396	71	20	posed	pose	VERB
ajst-32396	71	21	by	by	ADP
ajst-32396	71	22	highdimensional	highdimensional	ADJ
ajst-32396	71	23	data	datum	NOUN
ajst-32396	71	24	and	and	CCONJ
ajst-32396	71	25	realistic	realistic	ADJ
ajst-32396	71	26	noisy	noisy	ADJ
ajst-32396	71	27	environments	environment	NOUN
ajst-32396	71	28	.	.	PUNCT
ajst-32396	72	1	all	all	DET
ajst-32396	72	2	three	three	NUM
ajst-32396	72	3	methods	method	NOUN
ajst-32396	72	4	are	be	AUX
ajst-32396	72	5	effective	effective	ADJ
ajst-32396	72	6	for	for	ADP
ajst-32396	72	7	dimensionality	dimensionality	NOUN
ajst-32396	72	8	reduction	reduction	NOUN
ajst-32396	72	9	.	.	PUNCT
ajst-32396	73	1	the	the	DET
ajst-32396	73	2	selection	selection	NOUN
ajst-32396	73	3	among	among	ADP
ajst-32396	73	4	them	they	PRON
ajst-32396	73	5	should	should	AUX
ajst-32396	73	6	be	be	AUX
ajst-32396	73	7	guided	guide	VERB
ajst-32396	73	8	by	by	ADP
ajst-32396	73	9	the	the	DET
ajst-32396	73	10	nature	nature	NOUN
ajst-32396	73	11	of	of	ADP
ajst-32396	73	12	the	the	DET
ajst-32396	73	13	data	datum	NOUN
ajst-32396	73	14	and	and	CCONJ
ajst-32396	73	15	the	the	DET
ajst-32396	73	16	purpose	purpose	NOUN
ajst-32396	73	17	of	of	ADP
ajst-32396	73	18	the	the	DET
ajst-32396	73	19	analysis	analysis	NOUN
ajst-32396	73	20	:	:	PUNCT
ajst-32396	73	21	whether	whether	SCONJ
ajst-32396	73	22	the	the	DET
ajst-32396	73	23	aim	aim	NOUN
ajst-32396	73	24	is	be	AUX
ajst-32396	73	25	to	to	PART
ajst-32396	73	26	explain	explain	VERB
ajst-32396	73	27	maximum	maximum	ADJ
ajst-32396	73	28	variance	variance	NOUN
ajst-32396	73	29	(	(	PUNCT
ajst-32396	73	30	pca	pca	PROPN
ajst-32396	73	31	)	)	PUNCT
ajst-32396	73	32	,	,	PUNCT
ajst-32396	73	33	improve	improve	VERB
ajst-32396	73	34	interpretability	interpretability	NOUN
ajst-32396	73	35	(	(	PUNCT
ajst-32396	73	36	spca	spca	PROPN
ajst-32396	73	37	)	)	PUNCT
ajst-32396	73	38	,	,	PUNCT
ajst-32396	73	39	or	or	CCONJ
ajst-32396	73	40	withstand	withstand	VERB
ajst-32396	73	41	data	data	NOUN
ajst-32396	73	42	corruption	corruption	NOUN
ajst-32396	73	43	(	(	PUNCT
ajst-32396	73	44	rpca	rpca	PROPN
ajst-32396	73	45	)	)	PUNCT
ajst-32396	73	46	.	.	PUNCT
ajst-32396	74	1	as	as	SCONJ
ajst-32396	74	2	datasets	dataset	NOUN
ajst-32396	74	3	become	become	VERB
ajst-32396	74	4	larger	large	ADJ
ajst-32396	74	5	and	and	CCONJ
ajst-32396	74	6	more	more	ADV
ajst-32396	74	7	complex	complex	ADJ
ajst-32396	74	8	,	,	PUNCT
ajst-32396	74	9	the	the	DET
ajst-32396	74	10	fundamental	fundamental	ADJ
ajst-32396	74	11	ideas	idea	NOUN
ajst-32396	74	12	behind	behind	ADP
ajst-32396	74	13	pca	pca	PROPN
ajst-32396	74	14	—	—	PUNCT
ajst-32396	74	15	augmented	augment	VERB
ajst-32396	74	16	by	by	ADP
ajst-32396	74	17	modern	modern	ADJ
ajst-32396	74	18	adaptations	adaptation	NOUN
ajst-32396	74	19	for	for	ADP
ajst-32396	74	20	robustness	robustness	NOUN
ajst-32396	74	21	and	and	CCONJ
ajst-32396	74	22	sparsity	sparsity	NOUN
ajst-32396	74	23	—	—	PUNCT
ajst-32396	74	24	will	will	AUX
ajst-32396	74	25	continue	continue	VERB
ajst-32396	74	26	to	to	PART
ajst-32396	74	27	play	play	VERB
ajst-32396	74	28	a	a	DET
ajst-32396	74	29	vital	vital	ADJ
ajst-32396	74	30	role	role	NOUN
ajst-32396	74	31	in	in	ADP
ajst-32396	74	32	identifying	identify	VERB
ajst-32396	74	33	meaningful	meaningful	ADJ
ajst-32396	74	34	patterns	pattern	NOUN
ajst-32396	74	35	across	across	ADP
ajst-32396	74	36	diverse	diverse	ADJ
ajst-32396	74	37	types	type	NOUN
ajst-32396	74	38	of	of	ADP
ajst-32396	74	39	information	information	NOUN
ajst-32396	74	40	.	.	PUNCT
ajst-32396	75	1	227	227	NUM
ajst-32396	75	2	references	reference	NOUN
ajst-32396	75	3	[	[	X
ajst-32396	75	4	1	1	NUM
ajst-32396	75	5	]	]	PUNCT
ajst-32396	75	6	jolliffe	jolliffe	NOUN
ajst-32396	75	7	,	,	PUNCT
ajst-32396	75	8	i.	i.	NOUN
ajst-32396	75	9	t.	t.	PROPN
ajst-32396	75	10	(	(	PUNCT
ajst-32396	75	11	2002	2002	NUM
ajst-32396	75	12	)	)	PUNCT
ajst-32396	75	13	.	.	PUNCT
ajst-32396	76	1	principal	principal	ADJ
ajst-32396	76	2	component	component	NOUN
ajst-32396	76	3	analysis	analysis	NOUN
ajst-32396	76	4	(	(	PUNCT
ajst-32396	76	5	2nd	2nd	ADJ
ajst-32396	76	6	ed	ed	NOUN
ajst-32396	76	7	.	.	PUNCT
ajst-32396	76	8	)	)	PUNCT
ajst-32396	76	9	.	.	PUNCT
ajst-32396	77	1	springer	springer	NOUN
ajst-32396	77	2	-	-	PUNCT
ajst-32396	77	3	verlag	verlag	PROPN
ajst-32396	77	4	.	.	PUNCT
ajst-32396	78	1	[	[	X
ajst-32396	78	2	2	2	NUM
ajst-32396	78	3	]	]	PUNCT
ajst-32396	78	4	schölkopf	schölkopf	NOUN
ajst-32396	78	5	,	,	PUNCT
ajst-32396	78	6	b.	b.	PROPN
ajst-32396	78	7	,	,	PUNCT
ajst-32396	78	8	smola	smola	PROPN
ajst-32396	78	9	,	,	PUNCT
ajst-32396	78	10	a.	a.	PROPN
ajst-32396	78	11	,	,	PUNCT
ajst-32396	78	12	&	&	CCONJ
ajst-32396	78	13	müller	müller	PROPN
ajst-32396	78	14	,	,	PUNCT
ajst-32396	78	15	k.-r	k.-r	PROPN
ajst-32396	78	16	.	.	PUNCT
ajst-32396	79	1	(	(	PUNCT
ajst-32396	79	2	1998	1998	NUM
ajst-32396	79	3	)	)	PUNCT
ajst-32396	79	4	.	.	PUNCT
ajst-32396	80	1	nonlinear	nonlinear	ADJ
ajst-32396	80	2	component	component	NOUN
ajst-32396	80	3	analysis	analysis	NOUN
ajst-32396	80	4	as	as	ADP
ajst-32396	80	5	a	a	DET
ajst-32396	80	6	kernel	kernel	PROPN
ajst-32396	80	7	eigenvalue	eigenvalue	PROPN
ajst-32396	80	8	problem	problem	NOUN
ajst-32396	80	9	.	.	PUNCT
ajst-32396	81	1	neural	neural	ADJ
ajst-32396	81	2	computation	computation	NOUN
ajst-32396	81	3	,	,	PUNCT
ajst-32396	81	4	10(5	10(5	NUM
ajst-32396	81	5	)	)	PUNCT
ajst-32396	81	6	,	,	PUNCT
ajst-32396	81	7	1299–1319	1299–1319	NUM
ajst-32396	81	8	.	.	PUNCT
ajst-32396	82	1	[	[	X
ajst-32396	82	2	3	3	NUM
ajst-32396	82	3	]	]	X
ajst-32396	82	4	zou	zou	PROPN
ajst-32396	82	5	,	,	PUNCT
ajst-32396	82	6	h.	h.	PROPN
ajst-32396	82	7	,	,	PUNCT
ajst-32396	82	8	hastie	hastie	PROPN
ajst-32396	82	9	,	,	PUNCT
ajst-32396	82	10	t.	t.	PROPN
ajst-32396	82	11	,	,	PUNCT
ajst-32396	82	12	&	&	CCONJ
ajst-32396	82	13	tibshirani	tibshirani	PROPN
ajst-32396	82	14	,	,	PUNCT
ajst-32396	82	15	r.	r.	PROPN
ajst-32396	82	16	(	(	PUNCT
ajst-32396	82	17	2004	2004	NUM
ajst-32396	82	18	)	)	PUNCT
ajst-32396	82	19	.	.	PUNCT
ajst-32396	83	1	sparse	sparse	VERB
ajst-32396	83	2	principal	principal	ADJ
ajst-32396	83	3	component	component	NOUN
ajst-32396	83	4	analysis	analysis	NOUN
ajst-32396	83	5	[	[	X
ajst-32396	83	6	unpublished	unpublished	ADJ
ajst-32396	83	7	manuscript	manuscript	NOUN
ajst-32396	83	8	]	]	PUNCT
ajst-32396	83	9	.	.	PUNCT
ajst-32396	84	1	department	department	PROPN
ajst-32396	84	2	of	of	ADP
ajst-32396	84	3	statistics	statistic	NOUN
ajst-32396	84	4	,	,	PUNCT
ajst-32396	84	5	stanford	stanford	PROPN
ajst-32396	84	6	university	university	PROPN
ajst-32396	84	7	.	.	PUNCT
ajst-32396	85	1	[	[	X
ajst-32396	85	2	4	4	NUM
ajst-32396	85	3	]	]	PUNCT
ajst-32396	85	4	jolliffe	jolliffe	NOUN
ajst-32396	85	5	,	,	PUNCT
ajst-32396	85	6	i.	i.	PROPN
ajst-32396	85	7	t.	t.	PROPN
ajst-32396	85	8	,	,	PUNCT
ajst-32396	85	9	trendafilov	trendafilov	PROPN
ajst-32396	85	10	,	,	PUNCT
ajst-32396	85	11	n.	n.	PROPN
ajst-32396	85	12	t.	t.	PROPN
ajst-32396	85	13	,	,	PUNCT
ajst-32396	85	14	&	&	CCONJ
ajst-32396	85	15	uddin	uddin	PROPN
ajst-32396	85	16	,	,	PUNCT
ajst-32396	85	17	m.	m.	NOUN
ajst-32396	85	18	(	(	PUNCT
ajst-32396	85	19	2003	2003	NUM
ajst-32396	85	20	)	)	PUNCT
ajst-32396	85	21	.	.	PUNCT
ajst-32396	86	1	a	a	DET
ajst-32396	86	2	modified	modify	VERB
ajst-32396	86	3	principal	principal	ADJ
ajst-32396	86	4	component	component	NOUN
ajst-32396	86	5	technique	technique	NOUN
ajst-32396	86	6	based	base	VERB
ajst-32396	86	7	on	on	ADP
ajst-32396	86	8	the	the	DET
ajst-32396	86	9	lasso	lasso	NOUN
ajst-32396	86	10	.	.	PUNCT
ajst-32396	87	1	journal	journal	NOUN
ajst-32396	87	2	of	of	ADP
ajst-32396	87	3	computational	computational	ADJ
ajst-32396	87	4	and	and	CCONJ
ajst-32396	87	5	graphical	graphical	ADJ
ajst-32396	87	6	statistics	statistic	NOUN
ajst-32396	87	7	,	,	PUNCT
ajst-32396	87	8	12(3	12(3	NUM
ajst-32396	87	9	)	)	PUNCT
ajst-32396	87	10	,	,	PUNCT
ajst-32396	87	11	531–547	531–547	NUM
ajst-32396	87	12	.	.	PUNCT
ajst-32396	88	1	[	[	X
ajst-32396	88	2	5	5	NUM
ajst-32396	88	3	]	]	X
ajst-32396	88	4	wright	wright	PROPN
ajst-32396	88	5	,	,	PUNCT
ajst-32396	88	6	j.	j.	PROPN
ajst-32396	88	7	,	,	PUNCT
ajst-32396	88	8	ganesh	ganesh	PROPN
ajst-32396	88	9	,	,	PUNCT
ajst-32396	88	10	a.	a.	PROPN
ajst-32396	88	11	,	,	PUNCT
ajst-32396	88	12	rao	rao	PROPN
ajst-32396	88	13	,	,	PUNCT
ajst-32396	88	14	s.	s.	PROPN
ajst-32396	88	15	,	,	PUNCT
ajst-32396	88	16	peng	peng	PROPN
ajst-32396	88	17	,	,	PUNCT
ajst-32396	88	18	y.	y.	PROPN
ajst-32396	88	19	,	,	PUNCT
ajst-32396	88	20	&	&	CCONJ
ajst-32396	88	21	ma	ma	PROPN
ajst-32396	88	22	,	,	PUNCT
ajst-32396	88	23	y.	y.	PROPN
ajst-32396	88	24	(	(	PUNCT
ajst-32396	88	25	2009	2009	NUM
ajst-32396	88	26	)	)	PUNCT
ajst-32396	88	27	.	.	PUNCT
ajst-32396	89	1	robust	robust	ADJ
ajst-32396	89	2	principal	principal	ADJ
ajst-32396	89	3	component	component	NOUN
ajst-32396	89	4	analysis	analysis	NOUN
ajst-32396	89	5	:	:	PUNCT
ajst-32396	89	6	exact	exact	ADJ
ajst-32396	89	7	recovery	recovery	NOUN
ajst-32396	89	8	of	of	ADP
ajst-32396	89	9	corrupted	corrupted	ADJ
ajst-32396	89	10	low	low	ADJ
ajst-32396	89	11	-	-	PUNCT
ajst-32396	89	12	rank	rank	NOUN
ajst-32396	89	13	matrices	matrix	NOUN
ajst-32396	89	14	via	via	ADP
ajst-32396	89	15	convex	convex	PROPN
ajst-32396	89	16	optimization	optimization	NOUN
ajst-32396	89	17	.	.	PUNCT
ajst-32396	90	1	in	in	ADP
ajst-32396	90	2	advances	advance	NOUN
ajst-32396	90	3	in	in	ADP
ajst-32396	90	4	neural	neural	ADJ
ajst-32396	90	5	information	information	NOUN
ajst-32396	90	6	processing	processing	NOUN
ajst-32396	90	7	systems	system	NOUN
ajst-32396	90	8	(	(	PUNCT
ajst-32396	90	9	vol	vol	NOUN
ajst-32396	90	10	.	.	PROPN
ajst-32396	91	1	22	22	NUM
ajst-32396	91	2	,	,	PUNCT
ajst-32396	91	3	pp	pp	ADJ
ajst-32396	91	4	.	.	PUNCT
ajst-32396	92	1	2080–2088	2080–2088	NUM
ajst-32396	92	2	)	)	PUNCT
ajst-32396	92	3	.	.	PUNCT
ajst-32396	93	1	mit	mit	PROPN
ajst-32396	93	2	press	press	NOUN
ajst-32396	93	3	.	.	PUNCT
ajst-32396	94	1	[	[	X
ajst-32396	94	2	6	6	NUM
ajst-32396	94	3	]	]	PUNCT
ajst-32396	94	4	candès	candès	NOUN
ajst-32396	94	5	,	,	PUNCT
ajst-32396	94	6	e.	e.	PROPN
ajst-32396	94	7	j.	j.	PROPN
ajst-32396	94	8	,	,	PUNCT
ajst-32396	94	9	li	li	PROPN
ajst-32396	94	10	,	,	PUNCT
ajst-32396	94	11	x.	x.	PROPN
ajst-32396	94	12	,	,	PUNCT
ajst-32396	94	13	ma	ma	PROPN
ajst-32396	94	14	,	,	PUNCT
ajst-32396	94	15	y.	y.	PROPN
ajst-32396	94	16	,	,	PUNCT
ajst-32396	94	17	&	&	CCONJ
ajst-32396	94	18	wright	wright	PROPN
ajst-32396	94	19	,	,	PUNCT
ajst-32396	94	20	j.	j.	PROPN
ajst-32396	94	21	(	(	PUNCT
ajst-32396	94	22	2011	2011	NUM
ajst-32396	94	23	)	)	PUNCT
ajst-32396	94	24	.	.	PUNCT
ajst-32396	95	1	robust	robust	ADJ
ajst-32396	95	2	principal	principal	ADJ
ajst-32396	95	3	component	component	NOUN
ajst-32396	95	4	analysis	analysis	NOUN
ajst-32396	95	5	?	?	PUNCT
ajst-32396	96	1	journal	journal	NOUN
ajst-32396	96	2	of	of	ADP
ajst-32396	96	3	the	the	DET
ajst-32396	96	4	acm	acm	PROPN
ajst-32396	96	5	,	,	PUNCT
ajst-32396	96	6	58(3	58(3	NUM
ajst-32396	96	7	)	)	PUNCT
ajst-32396	96	8	,	,	PUNCT
ajst-32396	96	9	article	article	NOUN
ajst-32396	96	10	11	11	NUM
ajst-32396	96	11	.	.	PUNCT
ajst-32396	97	1	[	[	X
ajst-32396	97	2	7	7	X
ajst-32396	97	3	]	]	X
ajst-32396	97	4	bao	bao	PROPN
ajst-32396	97	5	,	,	PUNCT
ajst-32396	97	6	b.-k	b.-k	PROPN
ajst-32396	97	7	.	.	PUNCT
ajst-32396	97	8	,	,	PUNCT
ajst-32396	97	9	liu	liu	PROPN
ajst-32396	97	10	,	,	PUNCT
ajst-32396	97	11	g.	g.	PROPN
ajst-32396	97	12	,	,	PUNCT
ajst-32396	97	13	xu	xu	PROPN
ajst-32396	97	14	,	,	PUNCT
ajst-32396	97	15	c.	c.	PROPN
ajst-32396	97	16	,	,	PUNCT
ajst-32396	97	17	&	&	CCONJ
ajst-32396	97	18	yan	yan	PROPN
ajst-32396	97	19	,	,	PUNCT
ajst-32396	97	20	s.	s.	PROPN
ajst-32396	97	21	(	(	PUNCT
ajst-32396	97	22	2012	2012	NUM
ajst-32396	97	23	)	)	PUNCT
ajst-32396	97	24	.	.	PUNCT
ajst-32396	98	1	inductive	inductive	VERB
ajst-32396	98	2	robust	robust	ADJ
ajst-32396	98	3	principal	principal	ADJ
ajst-32396	98	4	component	component	NOUN
ajst-32396	98	5	analysis	analysis	NOUN
ajst-32396	98	6	.	.	PUNCT
ajst-32396	99	1	ieee	ieee	NOUN
ajst-32396	99	2	transactions	transaction	NOUN
ajst-32396	99	3	on	on	ADP
ajst-32396	99	4	image	image	NOUN
ajst-32396	99	5	processing	processing	NOUN
ajst-32396	99	6	,	,	PUNCT
ajst-32396	99	7	21(8	21(8	NUM
ajst-32396	99	8	)	)	PUNCT
ajst-32396	99	9	,	,	PUNCT
ajst-32396	99	10	3794–3800	3794–3800	NUM
ajst-32396	99	11	.	.	PUNCT
ajst-32396	100	1	[	[	X
ajst-32396	100	2	8	8	NUM
ajst-32396	100	3	]	]	X
ajst-32396	100	4	peng	peng	PROPN
ajst-32396	100	5	,	,	PUNCT
ajst-32396	100	6	c.	c.	PROPN
ajst-32396	100	7	,	,	PUNCT
ajst-32396	100	8	chen	chen	PROPN
ajst-32396	100	9	,	,	PUNCT
ajst-32396	100	10	y.	y.	PROPN
ajst-32396	100	11	,	,	PUNCT
ajst-32396	100	12	kang	kang	PROPN
ajst-32396	100	13	,	,	PUNCT
ajst-32396	100	14	z.	z.	PROPN
ajst-32396	100	15	,	,	PUNCT
ajst-32396	100	16	chen	chen	PROPN
ajst-32396	100	17	,	,	PUNCT
ajst-32396	100	18	c.	c.	PROPN
ajst-32396	100	19	,	,	PUNCT
ajst-32396	100	20	&	&	CCONJ
ajst-32396	100	21	cheng	cheng	PROPN
ajst-32396	100	22	,	,	PUNCT
ajst-32396	100	23	q.	q.	PROPN
ajst-32396	100	24	(	(	PUNCT
ajst-32396	100	25	2020	2020	NUM
ajst-32396	100	26	)	)	PUNCT
ajst-32396	100	27	.	.	PUNCT
ajst-32396	101	1	robust	robust	ADJ
ajst-32396	101	2	principal	principal	ADJ
ajst-32396	101	3	component	component	NOUN
ajst-32396	101	4	analysis	analysis	NOUN
ajst-32396	101	5	:	:	PUNCT
ajst-32396	101	6	a	a	DET
ajst-32396	101	7	factorization	factorization	NOUN
ajst-32396	101	8	-	-	PUNCT
ajst-32396	101	9	based	base	VERB
ajst-32396	101	10	approach	approach	NOUN
ajst-32396	101	11	with	with	ADP
ajst-32396	101	12	linear	linear	PROPN
ajst-32396	101	13	complexity	complexity	NOUN
ajst-32396	101	14	.	.	PUNCT
ajst-32396	102	1	information	information	NOUN
ajst-32396	102	2	sciences	sciences	PROPN
ajst-32396	102	3	,	,	PUNCT
ajst-32396	102	4	513	513	NUM
ajst-32396	102	5	,	,	PUNCT
ajst-32396	102	6	581–599	581–599	NUM
ajst-32396	102	7	.	.	PUNCT
ajst-32396	103	1	[	[	X
ajst-32396	103	2	9	9	NUM
ajst-32396	103	3	]	]	X
ajst-32396	103	4	ge	ge	PROPN
ajst-32396	103	5	,	,	PUNCT
ajst-32396	103	6	w.	w.	PROPN
ajst-32396	103	7	,	,	PUNCT
ajst-32396	103	8	hongzhe	hongzhe	ADV
ajst-32396	103	9	,	,	PUNCT
ajst-32396	103	10	x.	x.	PROPN
ajst-32396	103	11	,	,	PUNCT
ajst-32396	103	12	weibin	weibin	PROPN
ajst-32396	103	13	,	,	PUNCT
ajst-32396	103	14	z.	z.	PROPN
ajst-32396	103	15	,	,	PUNCT
ajst-32396	103	16	weilu	weilu	NOUN
ajst-32396	103	17	,	,	PUNCT
ajst-32396	103	18	z.	z.	PROPN
ajst-32396	103	19	,	,	PUNCT
ajst-32396	103	20	&	&	CCONJ
ajst-32396	103	21	baiyang	baiyang	PROPN
ajst-32396	103	22	,	,	PUNCT
ajst-32396	103	23	f.	f.	PROPN
ajst-32396	103	24	(	(	PUNCT
ajst-32396	103	25	2011	2011	NUM
ajst-32396	103	26	,	,	PUNCT
ajst-32396	103	27	april	april	PROPN
ajst-32396	103	28	)	)	PUNCT
ajst-32396	103	29	.	.	PUNCT
ajst-32396	104	1	multi	multi	ADJ
ajst-32396	104	2	-	-	ADJ
ajst-32396	104	3	kernel	kernel	ADJ
ajst-32396	104	4	pca	pca	PROPN
ajst-32396	104	5	based	base	VERB
ajst-32396	104	6	highdimensional	highdimensional	NOUN
ajst-32396	104	7	images	image	NOUN
ajst-32396	104	8	feature	feature	NOUN
ajst-32396	104	9	reduction	reduction	NOUN
ajst-32396	104	10	.	.	PUNCT
ajst-32396	105	1	in	in	ADP
ajst-32396	105	2	2011	2011	NUM
ajst-32396	105	3	international	international	ADJ
ajst-32396	105	4	conference	conference	NOUN
ajst-32396	105	5	on	on	ADP
ajst-32396	105	6	electric	electric	ADJ
ajst-32396	105	7	information	information	NOUN
ajst-32396	105	8	and	and	CCONJ
ajst-32396	105	9	control	control	NOUN
ajst-32396	105	10	engineering	engineering	NOUN
ajst-32396	105	11	(	(	PUNCT
ajst-32396	105	12	pp	pp	ADJ
ajst-32396	105	13	.	.	PUNCT
ajst-32396	105	14	5966–5969	5966–5969	NUM
ajst-32396	105	15	)	)	PUNCT
ajst-32396	105	16	.	.	PUNCT
ajst-32396	106	1	[	[	X
ajst-32396	106	2	10	10	NUM
ajst-32396	106	3	]	]	X
ajst-32396	106	4	cheng	cheng	PROPN
ajst-32396	106	5	,	,	PUNCT
ajst-32396	106	6	p.	p.	PROPN
ajst-32396	106	7	,	,	PUNCT
ajst-32396	106	8	li	li	PROPN
ajst-32396	106	9	,	,	PUNCT
ajst-32396	106	10	w.	w.	PROPN
ajst-32396	106	11	,	,	PUNCT
ajst-32396	106	12	&	&	CCONJ
ajst-32396	106	13	ogunbona	ogunbona	PROPN
ajst-32396	106	14	,	,	PUNCT
ajst-32396	106	15	p.	p.	NOUN
ajst-32396	106	16	(	(	PUNCT
ajst-32396	106	17	2009	2009	NUM
ajst-32396	106	18	,	,	PUNCT
ajst-32396	106	19	december	december	PROPN
ajst-32396	106	20	)	)	PUNCT
ajst-32396	106	21	.	.	PUNCT
ajst-32396	107	1	greedy	greedy	ADJ
ajst-32396	107	2	approximation	approximation	NOUN
ajst-32396	107	3	of	of	ADP
ajst-32396	107	4	kernel	kernel	PROPN
ajst-32396	107	5	pca	pca	PROPN
ajst-32396	107	6	by	by	ADP
ajst-32396	107	7	minimizing	minimize	VERB
ajst-32396	107	8	the	the	DET
ajst-32396	107	9	mapping	mapping	NOUN
ajst-32396	107	10	error	error	NOUN
ajst-32396	107	11	.	.	PUNCT
ajst-32396	108	1	in	in	ADP
ajst-32396	108	2	2009	2009	NUM
ajst-32396	108	3	digital	digital	ADJ
ajst-32396	108	4	image	image	NOUN
ajst-32396	108	5	computing	computing	NOUN
ajst-32396	108	6	:	:	PUNCT
ajst-32396	108	7	techniques	technique	NOUN
ajst-32396	108	8	and	and	CCONJ
ajst-32396	108	9	applications	application	NOUN
ajst-32396	108	10	(	(	PUNCT
ajst-32396	108	11	pp	pp	ADJ
ajst-32396	108	12	.	.	PUNCT
ajst-32396	108	13	303	303	NUM
ajst-32396	108	14	–	–	PUNCT
ajst-32396	108	15	308	308	NUM
ajst-32396	108	16	)	)	PUNCT
ajst-32396	108	17	.	.	PUNCT
ajst-32396	109	1	[	[	X
ajst-32396	109	2	11	11	NUM
ajst-32396	109	3	]	]	X
ajst-32396	109	4	wang	wang	PROPN
ajst-32396	109	5	,	,	PUNCT
ajst-32396	109	6	y.	y.	PROPN
ajst-32396	109	7	,	,	PUNCT
ajst-32396	109	8	&	&	CCONJ
ajst-32396	109	9	zhang	zhang	PROPN
ajst-32396	109	10	,	,	PUNCT
ajst-32396	109	11	y.	y.	PROPN
ajst-32396	109	12	(	(	PUNCT
ajst-32396	109	13	2010	2010	NUM
ajst-32396	109	14	)	)	PUNCT
ajst-32396	109	15	.	.	PUNCT
ajst-32396	110	1	facial	facial	ADJ
ajst-32396	110	2	recognition	recognition	NOUN
ajst-32396	110	3	is	be	AUX
ajst-32396	110	4	based	base	VERB
ajst-32396	110	5	on	on	ADP
ajst-32396	110	6	kernel	kernel	PROPN
ajst-32396	110	7	pca	pca	PROPN
ajst-32396	110	8	.	.	PUNCT
ajst-32396	111	1	2010	2010	NUM
ajst-32396	111	2	third	third	ADJ
ajst-32396	111	3	international	international	ADJ
ajst-32396	111	4	conference	conference	NOUN
ajst-32396	111	5	on	on	ADP
ajst-32396	111	6	intelligent	intelligent	ADJ
ajst-32396	111	7	networks	network	NOUN
ajst-32396	111	8	and	and	CCONJ
ajst-32396	111	9	intelligent	intelligent	ADJ
ajst-32396	111	10	systems	system	NOUN
ajst-32396	111	11	(	(	PUNCT
ajst-32396	111	12	pp	pp	ADJ
ajst-32396	111	13	.	.	PUNCT
ajst-32396	112	1	88	88	NUM
ajst-32396	112	2	-	-	SYM
ajst-32396	112	3	91	91	NUM
ajst-32396	112	4	)	)	PUNCT
ajst-32396	112	5	.	.	PUNCT
ajst-32396	113	1	ieee	ieee	NOUN
ajst-32396	113	2	.	.	PUNCT
ajst-32396	114	1	[	[	X
ajst-32396	114	2	12	12	NUM
ajst-32396	114	3	]	]	X
ajst-32396	114	4	lu	lu	PROPN
ajst-32396	114	5	,	,	PUNCT
ajst-32396	114	6	y.	y.	PROPN
ajst-32396	114	7	,	,	PUNCT
ajst-32396	114	8	gao	gao	PROPN
ajst-32396	114	9	,	,	PUNCT
ajst-32396	114	10	y.-l	y.-l	NOUN
ajst-32396	114	11	.	.	PUNCT
ajst-32396	114	12	,	,	PUNCT
ajst-32396	114	13	liu	liu	PROPN
ajst-32396	114	14	,	,	PUNCT
ajst-32396	114	15	j.-x	j.-x	NOUN
ajst-32396	114	16	.	.	PUNCT
ajst-32396	114	17	,	,	PUNCT
ajst-32396	114	18	wen	wen	PROPN
ajst-32396	114	19	,	,	PUNCT
ajst-32396	114	20	c.-g	c.-g	PROPN
ajst-32396	114	21	.	.	PROPN
ajst-32396	114	22	,	,	PUNCT
ajst-32396	114	23	wang	wang	PROPN
ajst-32396	114	24	,	,	PUNCT
ajst-32396	114	25	y.-x	y.-x	PROPN
ajst-32396	114	26	.	.	PROPN
ajst-32396	114	27	,	,	PUNCT
ajst-32396	114	28	&	&	CCONJ
ajst-32396	114	29	yu	yu	PROPN
ajst-32396	114	30	,	,	PUNCT
ajst-32396	114	31	j.	j.	PROPN
ajst-32396	114	32	(	(	PUNCT
ajst-32396	114	33	2016	2016	NUM
ajst-32396	114	34	)	)	PUNCT
ajst-32396	114	35	.	.	PUNCT
ajst-32396	115	1	characteristic	characteristic	ADJ
ajst-32396	115	2	gene	gene	NOUN
ajst-32396	115	3	selection	selection	NOUN
ajst-32396	115	4	via	via	ADP
ajst-32396	115	5	l2,1	l2,1	NOUN
ajst-32396	115	6	-	-	PUNCT
ajst-32396	115	7	norm	norm	NOUN
ajst-32396	115	8	sparse	sparse	ADJ
ajst-32396	115	9	principal	principal	ADJ
ajst-32396	115	10	component	component	NOUN
ajst-32396	115	11	analysis	analysis	NOUN
ajst-32396	115	12	.	.	PUNCT
ajst-32396	116	1	in	in	ADP
ajst-32396	116	2	2016	2016	NUM
ajst-32396	116	3	ieee	ieee	NOUN
ajst-32396	116	4	international	international	ADJ
ajst-32396	116	5	conference	conference	NOUN
ajst-32396	116	6	on	on	ADP
ajst-32396	116	7	bioinformatics	bioinformatics	NOUN
ajst-32396	116	8	and	and	CCONJ
ajst-32396	116	9	biomedicine	biomedicine	NOUN
ajst-32396	116	10	(	(	PUNCT
ajst-32396	116	11	bibm	bibm	NOUN
ajst-32396	116	12	)	)	PUNCT
ajst-32396	116	13	(	(	PUNCT
ajst-32396	116	14	pp	pp	ADV
ajst-32396	116	15	.	.	PUNCT
ajst-32396	117	1	1828–1833	1828–1833	NUM
ajst-32396	117	2	)	)	PUNCT
ajst-32396	117	3	.	.	PUNCT
ajst-32396	118	1	[	[	X
ajst-32396	118	2	13	13	NUM
ajst-32396	118	3	]	]	SYM
ajst-32396	118	4	yuan	yuan	NOUN
ajst-32396	118	5	,	,	PUNCT
ajst-32396	118	6	z.	z.	PROPN
ajst-32396	118	7	,	,	PUNCT
ajst-32396	118	8	xie	xie	PROPN
ajst-32396	118	9	,	,	PUNCT
ajst-32396	118	10	x.	x.	PROPN
ajst-32396	118	11	,	,	PUNCT
ajst-32396	118	12	ma	ma	PROPN
ajst-32396	118	13	,	,	PUNCT
ajst-32396	118	14	x.	x.	PROPN
ajst-32396	118	15	,	,	PUNCT
ajst-32396	118	16	&	&	CCONJ
ajst-32396	118	17	lam	lam	PROPN
ajst-32396	118	18	,	,	PUNCT
ajst-32396	118	19	k.-m	k.-m	PROPN
ajst-32396	118	20	.	.	PUNCT
ajst-32396	119	1	(	(	PUNCT
ajst-32396	119	2	2013	2013	NUM
ajst-32396	119	3	)	)	PUNCT
ajst-32396	119	4	.	.	PUNCT
ajst-32396	120	1	color	color	NOUN
ajst-32396	120	2	facial	facial	ADJ
ajst-32396	120	3	image	image	NOUN
ajst-32396	120	4	denoising	denoising	NOUN
ajst-32396	120	5	based	base	VERB
ajst-32396	120	6	on	on	ADP
ajst-32396	120	7	rpca	rpca	NOUN
ajst-32396	120	8	and	and	CCONJ
ajst-32396	120	9	noisy	noisy	ADJ
ajst-32396	120	10	pixel	pixel	PROPN
ajst-32396	120	11	detection	detection	NOUN
ajst-32396	120	12	.	.	PUNCT
ajst-32396	121	1	in	in	ADP
ajst-32396	121	2	2013	2013	NUM
ajst-32396	121	3	ieee	ieee	NOUN
ajst-32396	121	4	international	international	ADJ
ajst-32396	121	5	conference	conference	NOUN
ajst-32396	121	6	on	on	ADP
ajst-32396	121	7	acoustics	acoustic	NOUN
ajst-32396	121	8	,	,	PUNCT
ajst-32396	121	9	speech	speech	NOUN
ajst-32396	121	10	and	and	CCONJ
ajst-32396	121	11	signal	signal	NOUN
ajst-32396	121	12	processing	processing	NOUN
ajst-32396	121	13	(	(	PUNCT
ajst-32396	121	14	pp	pp	ADJ
ajst-32396	121	15	.	.	PUNCT
ajst-32396	121	16	2449	2449	NUM
ajst-32396	121	17	-	-	SYM
ajst-32396	121	18	2453	2453	NUM
ajst-32396	121	19	)	)	PUNCT
ajst-32396	121	20	.	.	PUNCT
ajst-32396	122	1	ieee	ieee	NOUN
ajst-32396	122	2	.	.	PUNCT
ajst-32396	123	1	[	[	X
ajst-32396	123	2	14	14	NUM
ajst-32396	123	3	]	]	X
ajst-32396	123	4	wang	wang	PROPN
ajst-32396	123	5	,	,	PUNCT
ajst-32396	123	6	y.	y.	PROPN
ajst-32396	123	7	,	,	PUNCT
ajst-32396	123	8	&	&	CCONJ
ajst-32396	123	9	zhu	zhu	PROPN
ajst-32396	123	10	,	,	PUNCT
ajst-32396	123	11	l.	l.	PROPN
ajst-32396	123	12	(	(	PUNCT
ajst-32396	123	13	2017	2017	NUM
ajst-32396	123	14	)	)	PUNCT
ajst-32396	123	15	.	.	PUNCT
ajst-32396	124	1	research	research	NOUN
ajst-32396	124	2	and	and	CCONJ
ajst-32396	124	3	implementation	implementation	NOUN
ajst-32396	124	4	of	of	ADP
ajst-32396	124	5	svd	svd	PROPN
ajst-32396	124	6	in	in	ADP
ajst-32396	124	7	machine	machine	NOUN
ajst-32396	124	8	learning	learning	NOUN
ajst-32396	124	9	.	.	PUNCT
ajst-32396	125	1	in	in	ADP
ajst-32396	125	2	*	*	NUM
ajst-32396	125	3	2017	2017	NUM
ajst-32396	125	4	ieee	ieee	NOUN
ajst-32396	125	5	/	/	SYM
ajst-32396	125	6	acis	acis	PROPN
ajst-32396	125	7	16th	16th	PROPN
ajst-32396	125	8	international	international	ADJ
ajst-32396	125	9	conference	conference	NOUN
ajst-32396	125	10	on	on	ADP
ajst-32396	125	11	computer	computer	NOUN
ajst-32396	125	12	and	and	CCONJ
ajst-32396	125	13	information	information	NOUN
ajst-32396	125	14	science	science	NOUN
ajst-32396	125	15	(	(	PUNCT
ajst-32396	125	16	icis	icis	PROPN
ajst-32396	125	17	)	)	PUNCT
ajst-32396	125	18	*	*	PUNCT
ajst-32396	125	19	(	(	PUNCT
ajst-32396	125	20	pp	pp	ADJ
ajst-32396	125	21	.	.	PUNCT
ajst-32396	125	22	471	471	NUM
ajst-32396	125	23	-	-	SYM
ajst-32396	125	24	475	475	NUM
ajst-32396	125	25	)	)	PUNCT
ajst-32396	125	26	.	.	PUNCT
ajst-32396	126	1	ieee	ieee	PROPN
ajst-32396	126	2	.	.	PUNCT