Feature extraction using maximum variance sparse mapping
Liu, Jin1,3; Li, Bo1,2,3; Zhang, Wen-Sheng3
2012-11-01
发表期刊NEURAL COMPUTING & APPLICATIONS
卷号21期号:8页码:1827-1833
文章类型Article
摘要In this paper, a multiple sub-manifold learning method-oriented classification is presented via sparse representation, which is named maximum variance sparse mapping. Based on the assumption that data with the same label locate on a sub-manifold and different class data reside in the corresponding sub-manifolds, the proposed algorithm can construct an objective function which aims to project the original data into a subspace with maximum sub-manifold distance and minimum manifold locality. Moreover, instead of setting the weights between any two points directly or obtaining those by a square optimal problem, the optimal weights in this new algorithm can be approached using L1 minimization. The proposed algorithm is efficient, which can be validated by experiments on some benchmark databases.
关键词Mvsm Sub-manifold Sparse Representation
WOS标题词Science & Technology ; Technology
关键词[WOS]UNSUPERVISED DISCRIMINANT PROJECTION ; DIMENSIONALITY REDUCTION ; FACE RECOGNITION ; PALM BIOMETRICS ; REPRESENTATION
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000309878400002
引用统计
被引频次:8[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/10742
专题精密感知与控制研究中心_精密感知与控制
作者单位1.Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China
2.Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430081, Peoples R China
3.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China
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Liu, Jin,Li, Bo,Zhang, Wen-Sheng. Feature extraction using maximum variance sparse mapping[J]. NEURAL COMPUTING & APPLICATIONS,2012,21(8):1827-1833.
APA Liu, Jin,Li, Bo,&Zhang, Wen-Sheng.(2012).Feature extraction using maximum variance sparse mapping.NEURAL COMPUTING & APPLICATIONS,21(8),1827-1833.
MLA Liu, Jin,et al."Feature extraction using maximum variance sparse mapping".NEURAL COMPUTING & APPLICATIONS 21.8(2012):1827-1833.
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