Sparse Weighted Canonical Correlation Analysis
文献类型:期刊论文
作者 | Min Wenwen1; Liu Juan1; Zhang Shihua2,3![]() |
刊名 | CHINESE JOURNAL OF ELECTRONICS
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出版日期 | 2018-05-01 |
卷号 | 27期号:3页码:459-466 |
关键词 | Canonical correlation analysis (CCA) Sparse canonical correlation analysis (SCCA) Sparse weighted CCA (SWCCA) Group LASSO regularized SWCCA Multi-view SWCCA |
ISSN号 | 1022-4653 |
DOI | 10.1049/cje.2017.08.004 |
英文摘要 | 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. |
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 |
语种 | 英语 |
WOS记录号 | WOS:000432512200003 |
出版者 | TECHNOLOGY EXCHANGE LIMITED HONG KONG |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/30390] ![]() |
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. |
入库方式: OAI收割
来源:数学与系统科学研究院
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