Adaptive total-variation for non-negative matrix factorization on manifold

doi:10.1016/j.patrec.2017.08.027

	Adaptive total-variation for non-negative matrix factorization on manifold
	Leng, Chengcai 1,2,3; Cai, Guorong 3,4; Yu, Dongdong3 ; Wang, Zongyue 4
发表期刊	PATTERN RECOGNITION LETTERS
	2017-10-01
卷号	98 页码:68-74
文章类型	Article
摘要	Non-negative matrix factorization (NMF) has been widely applied in information retrieval and computer vision. However, its performance has been restricted due to its limited tolerance to data noise, as well as its inflexibility in setting regularization parameters. In this paper, we propose a novel sparse matrix factorization method for data representation to solve these problems, termed Adaptive Total-Variation Constrained based Non-Negative Matrix Factorization on Manifold (ATV-NMF). The proposed ATV can adaptively choose the anisotropic smoothing scheme based on the gradient information of data to denoise or preserve feature details by incorporating adaptive total variation into the factorization process. Notably, the manifold graph regularization is also incorporated into NMF, which can discover intrinsic geometrical structure of data to enhance the discriminability. Experimental results demonstrate that the proposed method is very effective for data clustering in comparison to the state-of-the-art algorithms on several standard benchmarks. (C) 2017 Elsevier B. V. All rights reserved.
关键词	Adaptive Total Variation Non-negative Matrix Factorization Manifold Learning
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.patrec.2017.08.027
关键词[WOS]	NONLINEAR DIMENSIONALITY REDUCTION ; BIOLUMINESCENCE TOMOGRAPHY ; FACE RECOGNITION ; REGULARIZATION ; REPRESENTATION ; ALGORITHMS ; FRAMEWORK ; PARTS
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:000411766300010
引用统计	被引频次：16[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/173211/20733
专题	中国科学院分子影像重点实验室
作者单位	1.Northwest Univ Xian, Sch Math, Xian 710127, Shaanxi, Peoples R China 2.Nanchang Hangkong Univ, Sch Math & Informat Sci, Nanchang 330063, Jiangxi, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Jimei Univ, Coll Comp Engn, Xiamen 361021, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Leng, Chengcai,Cai, Guorong,Yu, Dongdong,et al. Adaptive total-variation for non-negative matrix factorization on manifold[J]. PATTERN RECOGNITION LETTERS,2017,98:68-74.
APA	Leng, Chengcai,Cai, Guorong,Yu, Dongdong,&Wang, Zongyue.(2017).Adaptive total-variation for non-negative matrix factorization on manifold.PATTERN RECOGNITION LETTERS,98,68-74.
MLA	Leng, Chengcai,et al."Adaptive total-variation for non-negative matrix factorization on manifold".PATTERN RECOGNITION LETTERS 98(2017):68-74.