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Nonnegative class-specific entropy component analysis with adaptive step search criterion
Miao Cheng; Chi-Man Pun; Yuan Yan Tang
2014-02-01
Source PublicationPattern Analysis and Applications
ISSN1433-7541
Volume17Issue:1Pages:113-127
Abstract

Nonnegative learning aims to learn the part-based representation of nonnegative data and receives much attention in recent years. Nonnegative matrix factorization has been popular to make nonnegative learning applicable, which can also be explained as an optimization problem with bound constraints. In order to exploit the informative components hidden in nonnegative patterns, a novel nonnegative learning method, termed nonnegative class-specific entropy component analysis, is developed in this work. Distinguish from the existing methods, the proposed method aims to conduct the general objective functions, and the conjugate gradient technique is applied to enhance the iterative optimization. In view of the development, a general nonnegative learning framework is presented to deal with the nonnegative optimization problem with general objective costs. Owing to the general objective costs and the nonnegative bound constraints, the diseased nonnegative learning problem usually occurs. To address this limitation, a modified line search criterion is proposed, which prevents the null trap with insured conditions while keeping the feasible step descendent. In addition, the numerical stopping rule is employed to achieve optimized efficiency, instead of the popular gradient-based one. Experiments on face recognition with varieties of conditions reveal that the proposed method possesses better performance over other methods. 

KeywordDiseased Nonnegative Learning Problem General Objective Functions Line Search Nonnegative Learning
DOIhttps://doi.org/10.1007/s10044-011-0258-2
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000330839400009
PublisherSPRINGER, 233 SPRING ST, NEW YORK, NY 10013 USA
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被引频次[WOS]:2   [WOS记录]     [WOS相关记录]
Document TypeJournal article
专题DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationDepartment of Computer and Information Science, University of Macau, Taipa, Macau
First Author AffilicationUniversity of Macau
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Miao Cheng,Chi-Man Pun,Yuan Yan Tang. Nonnegative class-specific entropy component analysis with adaptive step search criterion[J]. Pattern Analysis and Applications,2014,17(1):113-127.
APA Miao Cheng,Chi-Man Pun,&Yuan Yan Tang.(2014).Nonnegative class-specific entropy component analysis with adaptive step search criterion.Pattern Analysis and Applications,17(1),113-127.
MLA Miao Cheng,et al."Nonnegative class-specific entropy component analysis with adaptive step search criterion".Pattern Analysis and Applications 17.1(2014):113-127.
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