Structure preserving non-negative matrix factorization for dimensionality reduction

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	Structure preserving non-negative matrix factorization for dimensionality reduction
	Li, Zechao; Liu, Jing; Lu, Hanqing
刊名	COMPUTER VISION AND IMAGE UNDERSTANDING
	2013-09-01
卷号	117 期号:9 页码:1175-1189
关键词	Dimensionality reduction Non-negative matrix factorization Structure preserving Basis compactness Multiplicative update algorithm
英文摘要	The problem of dimensionality reduction is to map data from high dimensional spaces to low dimensional spaces. In the process of dimensionality reduction, the data structure, which is helpful to discover the latent semantics and simultaneously respect the intrinsic geometric structure, should be preserved. In this paper, to discover a low-dimensional embedding space with the nature of structure preservation and basis compactness, we propose a novel dimensionality reduction algorithm, called Structure Preserving Non-negative Matrix Factorization (SPNMF). In SPNMF, three kinds of constraints, namely local affinity, distant repulsion, and embedding basis redundancy elimination, are incorporated into the NMF framework. SPNMF is formulated as an optimization problem and solved by an effective iterative multiplicative update algorithm. The convergence of the proposed update solutions is proved. Extensive experiments on both synthetic data and six real world data sets demonstrate the encouraging performance of the proposed algorithm in comparison to the state-of-the-art algorithms, especially some related works based on NMF. Moreover, the convergence of the proposed updating rules is experimentally validated. (C) 2013 Elsevier Inc. All rights reserved.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	DISCRIMINANT-ANALYSIS ; LAPLACIAN EIGENMAPS ; OBJECT RECOGNITION ; COMPONENT ANALYSIS ; FACE RECOGNITION ; REPRESENTATION ; PARTS ; ILLUMINATION ; PCA ; LDA
收录类别	SCI
语种	英语
WOS记录号	WOS:000321724300019
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3337]
专题	自动化研究所_模式识别国家重点实验室_图像与视频分析团队
作者单位	Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Zechao,Liu, Jing,Lu, Hanqing. Structure preserving non-negative matrix factorization for dimensionality reduction[J]. COMPUTER VISION AND IMAGE UNDERSTANDING,2013,117(9):1175-1189.
APA	Li, Zechao,Liu, Jing,&Lu, Hanqing.(2013).Structure preserving non-negative matrix factorization for dimensionality reduction.COMPUTER VISION AND IMAGE UNDERSTANDING,117(9),1175-1189.
MLA	Li, Zechao,et al."Structure preserving non-negative matrix factorization for dimensionality reduction".COMPUTER VISION AND IMAGE UNDERSTANDING 117.9(2013):1175-1189.