A Constrained Algorithm Based NMFα for Image Representation
Nonnegative matrix factorization (NMF) is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for imag...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2014/179129 |
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| _version_ | 1850165672179400704 |
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| author | Chenxue Yang Tao Li Mao Ye Zijian Liu Jiao Bao |
| author_facet | Chenxue Yang Tao Li Mao Ye Zijian Liu Jiao Bao |
| author_sort | Chenxue Yang |
| collection | DOAJ |
| description | Nonnegative matrix factorization (NMF) is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT) conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets. |
| format | Article |
| id | doaj-art-ee808fb17d664c2887c2ebba7c1c62a1 |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-ee808fb17d664c2887c2ebba7c1c62a12025-08-20T02:21:41ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2014-01-01201410.1155/2014/179129179129A Constrained Algorithm Based NMFα for Image RepresentationChenxue Yang0Tao Li1Mao Ye2Zijian Liu3Jiao Bao4School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Science, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaNonnegative matrix factorization (NMF) is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT) conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.http://dx.doi.org/10.1155/2014/179129 |
| spellingShingle | Chenxue Yang Tao Li Mao Ye Zijian Liu Jiao Bao A Constrained Algorithm Based NMFα for Image Representation Discrete Dynamics in Nature and Society |
| title | A Constrained Algorithm Based NMFα for Image Representation |
| title_full | A Constrained Algorithm Based NMFα for Image Representation |
| title_fullStr | A Constrained Algorithm Based NMFα for Image Representation |
| title_full_unstemmed | A Constrained Algorithm Based NMFα for Image Representation |
| title_short | A Constrained Algorithm Based NMFα for Image Representation |
| title_sort | constrained algorithm based nmfα for image representation |
| url | http://dx.doi.org/10.1155/2014/179129 |
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