Supervised learning of sparse context reconstruction coefficients for data representation and classification

doi:10.1007/s00521-015-2042-5

NTSC-IR

	Supervised learning of sparse context reconstruction coefficients for data representation and classification
	Liu, Xuejie 1; Wang, Jingbin 2,3; Yin, Ming 4; Edwards, Benjamin 5; Xu, Peijuan 1
	2017
发表期刊	NEURAL COMPUTING & APPLICATIONS
ISSN	0941-0643
卷号	28 期号:1 页码:135-143
摘要	Context of data points, which is usually defined as the other data points in a data set, has been found to paly important roles in data representation and classification. In this paper, we study the problem of using context of a data point for its classification problem. Our work is inspired by the observation that actually only very few data points are critical in the context of a data point for its representation and classification. We propose to represent a data point as the sparse linear combination of its context and learn the sparse context in a supervised way to increase its discriminative ability. To this end, we proposed a novel formulation for context learning, by modeling the learning of context parameter and classifier in a unified objective, and optimizing it with an alternative strategy in an iterative algorithm. Experiments on three benchmark data set show its advantage over state-of-the-art context-based data representation and classification methods.
关键词	Pattern classification Data representation Context Nearest neighbors Sparse regularization
资助者	Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China
DOI	10.1007/s00521-015-2042-5
关键词[WOS]	SUPPORT VECTOR MACHINES ; NONNEGATIVE MATRIX FACTORIZATION ; FACE RECOGNITION ; FEATURE-SELECTION ; COMPUTER VISION ; INFORMATION ; SPACE ; RETRIEVAL ; SYSTEM
语种	英语
资助项目	Fundamental Research Funds of Jilin University, China[450060491509]
资助者	Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China ; Fundamental Research Funds of Jilin University, China
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000392419100011
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://210.72.145.45/handle/361003/11339
专题	中国科学院国家授时中心
通讯作者	Yin, Ming
作者单位	1.Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China 2.Chinese Acad Sci, Natl Time Serv Ctr, Xian 710600, Peoples R China 3.Chinese Acad Sci, Grad Univ, Beijing 100039, Peoples R China 4.Eskisehir Osmangazi Univ, Dept Math & Comp Sci, TR-26480 Eskisehir, Turkey 5.Sam Houston State Univ, Dept Comp Sci, Huntsville, TX 77341 USA
推荐引用方式 GB/T 7714	Liu, Xuejie,Wang, Jingbin,Yin, Ming,et al. Supervised learning of sparse context reconstruction coefficients for data representation and classification[J]. NEURAL COMPUTING & APPLICATIONS,2017,28(1):135-143.
APA	Liu, Xuejie,Wang, Jingbin,Yin, Ming,Edwards, Benjamin,&Xu, Peijuan.(2017).Supervised learning of sparse context reconstruction coefficients for data representation and classification.NEURAL COMPUTING & APPLICATIONS,28(1),135-143.
MLA	Liu, Xuejie,et al."Supervised learning of sparse context reconstruction coefficients for data representation and classification".NEURAL COMPUTING & APPLICATIONS 28.1(2017):135-143.