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Multi-view subspace clustering with intactness-aware similarity

文献类型：期刊论文

作者Wang, Xiaobo1; Lei, Zhen2,3; Guo, Xiaojie4; Zhang, Changqing4; Shi, Hailin1; Li, Stan Z.2,3,5
刊名PATTERN RECOGNITION
出版日期2019-04-01
卷号88页码:50-63
关键词Intact space Intactness-aware similarity Multi-view subspace clustering
ISSN号0031-3203
DOI10.1016/j.patcog.2018.09.009
通讯作者Lei, Zhen(zlei@nlpr.ia.ac.cn)
英文摘要Multi-view subspace clustering, which aims to partition a set of multi-source data into their underlying groups, has recently attracted intensive attention from the communities of pattern recognition and data mining. This paper proposes a novel multi-view subspace clustering model that attempts to form an informative intactness-aware similarity based on the intact space learning technique. More specifically, we learn an intact space by integrating encoded complementary information. An informative similarity matrix is simultaneously constructed, which enforces the constructed similarity to have maximum dependence with its latent intact points by adopting the Hilbert-Schmidt Independence Criterion (HSIC). A new explanation on the advantages of such intactness-aware similarity has been provided (i.e., the similarity is learned according to the local connectivity). To effectively and efficiently seek the optimal solution of the associated problem, a new ADMM based algorithm is designed. Moreover, to show the merit of the proposed joint optimization, we also conduct the clustering in two separated steps. Extensive experimental results on six benchmark datasets are provided to reveal the effectiveness of the proposed algorithm and its superior performance over other state-of-the-art alternatives. (C) 2018 Published by Elsevier Ltd.
WOS关键词ALGORITHM ; FUSION
资助项目National Key Research and Development Plan[2016YFC0801002] ; Chinese National Natural Science Foundation[61876178] ; Chinese National Natural Science Foundation[61473291] ; Chinese National Natural Science Foundation[61572501] ; Chinese National Natural Science Foundation[61502491] ; Chinese National Natural Science Foundation[61572536] ; Science and Technology Development Fund of Macau[151/2017/A] ; Science and Technology Development Fund of Macau[152/2017/A] ; AuthenMetric RD Funds
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000457666900005
出版者ELSEVIER SCI LTD
资助机构National Key Research and Development Plan ; Chinese National Natural Science Foundation ; Science and Technology Development Fund of Macau ; AuthenMetric RD Funds
源URL[http://ir.ia.ac.cn/handle/173211/25269]  
专题自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心
通讯作者Lei, Zhen
作者单位1.JD AI Res, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, CBSR, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China
4.Tianjin Univ, Tianjin, Peoples R China
5.Macau Univ Sci & Technol, Fac Informat Technol, Taipa, Macao, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Xiaobo,Lei, Zhen,Guo, Xiaojie,et al. Multi-view subspace clustering with intactness-aware similarity[J]. PATTERN RECOGNITION,2019,88:50-63.
APA Wang, Xiaobo,Lei, Zhen,Guo, Xiaojie,Zhang, Changqing,Shi, Hailin,&Li, Stan Z..(2019).Multi-view subspace clustering with intactness-aware similarity.PATTERN RECOGNITION,88,50-63.
MLA Wang, Xiaobo,et al."Multi-view subspace clustering with intactness-aware similarity".PATTERN RECOGNITION 88(2019):50-63.

入库方式： OAI收割

来源：自动化研究所

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