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Constrained Nonnegative Matrix Factorization for Image Representation
Liu, Haifeng1; Wu, Zhaohui1; Li, Xuelong2; Cai, Deng3; Huang, Thomas S.4
Department光学影像分析与学习中心
2012-07-01
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN0162-8828
Volume34Issue:7Pages:1299-1311
Contribution Rank3
AbstractNonnegative matrix factorization (NMF) is a popular technique for finding parts-based, linear representations of nonnegative data. It has been successfully applied in a wide range of applications such as pattern recognition, information retrieval, and computer vision. However, NMF is essentially an unsupervised method and cannot make use of label information. In this paper, we propose a novel semi-supervised matrix decomposition method, called Constrained Nonnegative Matrix Factorization (CNMF), which incorporates the label information as additional constraints. Specifically, we show how explicitly combining label information improves the discriminating power of the resulting matrix decomposition. We explore the proposed CNMF method with two cost function formulations and provide the corresponding update solutions for the optimization problems. Empirical experiments demonstrate the effectiveness of our novel algorithm in comparison to the state-of-the-art approaches through a set of evaluations based on real-world applications.
SubtypeArticle
KeywordNonnegative Matrix Factorization Semi-supervised Learning Dimension Reduction Clustering
Subject AreaComputer Science
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TPAMI.2011.217
Indexed BySCI ; EI
WOS KeywordGRADIENT ; MANIFOLD ; PARTS
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000304138300004
Citation statistics
Cited Times:181[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/20255
Collection光学影像学习与分析中心
Affiliation1.Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China
2.Chinese Acad Sci, Ctr Opt IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
3.Zhejiang Univ, State Key Lab CAD&CG, Coll Comp Sci, Hangzhou 310058, Zhejiang, Peoples R China
4.Univ Illinois, Dept Elect & Comp Engn, Beckman Inst Adv Sci & Technol, Urbana, IL 61801 USA
Recommended Citation
GB/T 7714
Liu, Haifeng,Wu, Zhaohui,Li, Xuelong,et al. Constrained Nonnegative Matrix Factorization for Image Representation[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2012,34(7):1299-1311.
APA Liu, Haifeng,Wu, Zhaohui,Li, Xuelong,Cai, Deng,&Huang, Thomas S..(2012).Constrained Nonnegative Matrix Factorization for Image Representation.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,34(7),1299-1311.
MLA Liu, Haifeng,et al."Constrained Nonnegative Matrix Factorization for Image Representation".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 34.7(2012):1299-1311.
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