Sparse Weighted Canonical Correlation Analysis

doi:10.1049/cje.2017.08.004

CSpace > 应用数学研究所

	Sparse Weighted Canonical Correlation Analysis
	Min Wenwen 1; Liu Juan 1; Zhang Shihua2,3
	2018-05-01
发表期刊	CHINESE JOURNAL OF ELECTRONICS
ISSN	1022-4653
卷号	27 期号:3 页码:459-466
摘要	Given two data matrices X and Y, Sparse canonical correlation analysis (SCCA) is to seek two sparse canonical vectors u and v to maximize the correlation between Xu and Yv. Classical and sparse Canonical correlation analysis (CCA) models consider the contribution of all the samples of data matrices and thus cannot identify an underlying specific subset of samples. We propose a novel Sparse weighted canonical correlation analysis (SWCCA), where weights are used for regularizing different samples. We solve the L-0-regularized SWCCA (L-0-SWCCA) using an alternating iterative algorithm. We apply L-0-SWCCA to synthetic data and real-world data to demonstrate its effectiveness and superiority compared to related methods. We consider also SWCCA with different penalties like Least absolute shrinkage and selection operator (LASSO) and Group LASSO, and extend it for integrating more than three data matrices.
关键词	Canonical correlation analysis (CCA) Sparse canonical correlation analysis (SCCA) Sparse weighted CCA (SWCCA) Group LASSO regularized SWCCA Multi-view SWCCA
DOI	10.1049/cje.2017.08.004
语种	英语
资助项目	National Natural Science Foundation of China[61422309] ; National Natural Science Foundation of China[61379092] ; National Natural Science Foundation of China[61621003] ; National Natural Science Foundation of China[11661141019] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB13040600] ; National Science Foundation of Jiangsu Province[BK20161249] ; Fundamental Research Funds for the Central Universities[2042017KF0233] ; CAS Frontier Science Research Key Project for Top Young Scientist[QYZDB-SSW-SYS008] ; Key Laboratory of Random Complex Structures and Data Science, CAS[2008DP173182]
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000432512200003
出版者	TECHNOLOGY EXCHANGE LIMITED HONG KONG
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/30391
专题	应用数学研究所
通讯作者	Min Wenwen
作者单位	1.Wuhan Univ, Sch Comp, State Key Lab Software Engn, Wuhan 430072, Hubei, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Min Wenwen,Liu Juan,Zhang Shihua. Sparse Weighted Canonical Correlation Analysis[J]. CHINESE JOURNAL OF ELECTRONICS,2018,27(3):459-466.
APA	Min Wenwen,Liu Juan,&Zhang Shihua.(2018).Sparse Weighted Canonical Correlation Analysis.CHINESE JOURNAL OF ELECTRONICS,27(3),459-466.
MLA	Min Wenwen,et al."Sparse Weighted Canonical Correlation Analysis".CHINESE JOURNAL OF ELECTRONICS 27.3(2018):459-466.