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Multi-view Clustering via Pairwise Sparse Subspace Representation. Neurocomputing
Qiyue Yin; Shu Wu; Ran He(赫然); Liang Wang; Wu, Shu
Source PublicationNEUROCOMPUTING
2015-05-25
Volume156Issue:156Pages:12-21
SubtypeArticle
AbstractMulti-view clustering, which aims to cluster datasets with multiple sources of information, has a wide range of applications in the communities of data mining and pattern recognition. Generally, it makes use of the complementary information embedded in multiple views to improve clustering performance. Recent methods usually find a low-dimensional embedding of multi-view data, but often ignore some useful prior information that can be utilized to better discover the latent group structure of multi-view data. To alleviate this problem, a novel pairwise sparse subspace representation model for multi-view clustering is proposed in this paper. The objective function of our model mainly includes two parts. The first part aims to harness prior information to achieve a sparse representation of each high-dimensional data point with respect to other data points in the same view. The second part aims to maximize the correlation between the representations of different views. An alternating minimization method is provided as an efficient solution for the proposed multi-view clustering algorithm. A detailed theoretical analysis is also conducted to guarantee the convergence of the proposed method. Moreover, we show that the must-link and cannot-link constraints can be naturally integrated into the proposed model to obtain a link constrained multi-view clustering model. Extensive experiments on five real world datasets demonstrate that the proposed model performs better than several state-of-the-art multi-view clustering methods. (C) 2015 Elsevier B.V. All rights reserved.
KeywordMulti-view Clustering Subspace Clustering Pairwise Sparse Representation
WOS HeadingsScience & Technology ; Technology
WOS KeywordSEGMENTATION ; ALGORITHM ; ROBUST
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000351978100002
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8104
Collection智能感知与计算研究中心
Corresponding AuthorWu, Shu
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Qiyue Yin,Shu Wu,Ran He,et al. Multi-view Clustering via Pairwise Sparse Subspace Representation. Neurocomputing[J]. NEUROCOMPUTING,2015,156(156):12-21.
APA Qiyue Yin,Shu Wu,Ran He,Liang Wang,&Wu, Shu.(2015).Multi-view Clustering via Pairwise Sparse Subspace Representation. Neurocomputing.NEUROCOMPUTING,156(156),12-21.
MLA Qiyue Yin,et al."Multi-view Clustering via Pairwise Sparse Subspace Representation. Neurocomputing".NEUROCOMPUTING 156.156(2015):12-21.
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