Discriminant Projective Non-Negative Matrix Factorization

Guan, N; Zhang, XS; Luo, Z; Tao, D; Yang, X

Discriminant Projective Non-Negative Matrix Factorization

Guan, N Zhang, XS Luo, Z Tao, D Yang, X

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Publisher:: Public Library Science
Publication Type:: Journal Article
Citation:: Guan, Naiyang et al. 2013, 'Discriminant Projective Non-Negative Matrix Factorization', Plos One, vol. 8, no. 12, pp. e83291-1-e83291-12.
Issue Date:: 2013

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Field	Value	Language
dc.contributor.author	Guan, N	en_US
dc.contributor.author	Zhang, XS	en_US
dc.contributor.author	Luo, Z	en_US
dc.contributor.author	Tao, D	en_US
dc.contributor.author	Yang, X	en_US
dc.date.accessioned	2014-04-14T02:46:12Z
dc.date.available	2014-04-14T02:46:12Z
dc.date.issued	2013	en_US
dc.identifier	2013000950	en_US
dc.identifier.citation	Guan, Naiyang et al. 2013, 'Discriminant Projective Non-Negative Matrix Factorization', Plos One, vol. 8, no. 12, pp. e83291-1-e83291-12.	en_US
dc.identifier.issn	1932-6203	en_US
dc.identifier.other	C1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26574
dc.description.abstract	Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W-T X as their coefficients, i.e., X approximate to WWT X. Since PNMF	en_US
dc.publisher	Public Library Science	en_US
dc.relation.ispartof	Plos One	en_US
dc.relation.ispartof	Verified OK	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1371/journal.pone.0083291	en_US
dc.subject	Recognition; Image; Framework; Variables; Parts; Pca	en_US
dc.subject.classification	Artificial Intelligence and Image Processing	en_US
dc.title	Discriminant Projective Non-Negative Matrix Factorization	en_US
dc.type	Journal article
utslib.citation.volume	8	en_US
utslib.citation.number	12	en_US
utslib.location	San Francisco	en_US
utslib.citation.startpage	e83291-1	en_US
utslib.citation.endpage	e83291-12	en_US
utslib.identifier.org	FEIT.Faculty of Engineering & Information Technology	en_US
utslib.for	080100	en_US
utslib.percentage	100	en_US
utslib.copyright.status	open_access

Abstract:

Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W-T X as their coefficients, i.e., X approximate to WWT X. Since PNMF

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http://hdl.handle.net/10453/26574