CASIA OpenIR
On connections between Renyi entropy Principal Component Analysis, kernel learning and graph embedding
Ran, Zhi-Yong1; Wang, Wei2; Hu, Bao-Gang3
Source PublicationPATTERN RECOGNITION LETTERS
ISSN0167-8655
2018-09-01
Volume112Pages:125-130
SubtypeArticle
AbstractIn this paper, we study the connections between Renyi entropy PCA, kernel learning and graph embedding. A natural complementary formulation of maximum entropy PCA, namely minimum error entropy PCA, is presented. These two formulations can be combined together to give a two-fold understanding of Renyi entropy PCA. Further, we establish connections between Renyi entropy PCA, kernel learning and graph embedding, and propose a generalized graph embedding framework that unifies a variety of existing algorithms. This proposed framework essentially covers previous graph embedding framework, and partially answers the problem of how to make use of high order statistics of data in dimensionality reduction. The theoretic development enables a close relationship between information theoretic learning, kernel learning and graph embedding. (c) 2018 Elsevier B.V. All rights reserved.
KeywordRenyi Entropy Pca Kernel Learning Graph Embedding
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.patrec.2018.06.011
WOS KeywordNONLINEAR DIMENSIONALITY REDUCTION ; FRAMEWORK
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61502466 ; 61503365)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000443950800018
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27917
Collection中国科学院自动化研究所
Corresponding AuthorWang, Wei
Affiliation1.Chongqing Univ Posts & Telecommun, Chongqing 400065, Peoples R China
2.Chinese Acad Sci, Inst Software, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Ran, Zhi-Yong,Wang, Wei,Hu, Bao-Gang. On connections between Renyi entropy Principal Component Analysis, kernel learning and graph embedding[J]. PATTERN RECOGNITION LETTERS,2018,112:125-130.
APA Ran, Zhi-Yong,Wang, Wei,&Hu, Bao-Gang.(2018).On connections between Renyi entropy Principal Component Analysis, kernel learning and graph embedding.PATTERN RECOGNITION LETTERS,112,125-130.
MLA Ran, Zhi-Yong,et al."On connections between Renyi entropy Principal Component Analysis, kernel learning and graph embedding".PATTERN RECOGNITION LETTERS 112(2018):125-130.
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