Knowledge Commons of Institute of Automation，CAS
| Multi-view subspace clustering with intactness-aware similarity | |
Wang, Xiaobo1 ; Lei, Zhen2,3; Guo, Xiaojie4; Zhang, Changqing4; Shi, Hailin1; Li, Stan Z.2,3,5
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| Source Publication | PATTERN RECOGNITION
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| ISSN | 0031-3203 |
| 2019-04-01 | |
| Volume | 88Pages:50-63 |
| Corresponding Author | Lei, Zhen(zlei@nlpr.ia.ac.cn) |
| Abstract | 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. |
| Keyword | Intact space Intactness-aware similarity Multi-view subspace clustering |
| DOI | 10.1016/j.patcog.2018.09.009 |
| WOS Keyword | ALGORITHM ; FUSION |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 ; 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 |
| Funding Organization | National Key Research and Development Plan ; Chinese National Natural Science Foundation ; Science and Technology Development Fund of Macau ; AuthenMetric RD Funds |
| WOS Research Area | Computer Science ; Engineering |
| WOS Subject | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS ID | WOS:000457666900005 |
| Publisher | ELSEVIER SCI LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/25270 |
| Collection | 中国科学院自动化研究所 |
| Corresponding Author | Lei, Zhen |
| Affiliation | 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 |
| Corresponding Author Affilication | Institute of Automation, Chinese Academy of Sciences; Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| Recommended Citation 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. |
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