Institute of Computing Technology, Chinese Academy IR
Split Multiplicative Multi-View Subspace Clustering | |
Yang, Zhiyong1,2; Xu, Qianqian3; Zhang, Weigang4,5; Cao, Xiaochun1,2,6; Huang, Qingming3,7,8 | |
2019-10-01 | |
发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING |
ISSN | 1057-7149 |
卷号 | 28期号:10页码:5147-5160 |
摘要 | Various subspace clustering methods have been successively developed to process multi-view datasets. Mast of the existing methods try to obtain a consensus structure coefficient matrix based on view-specific subspace recoveries. However, since view-specific structures contain individualized components that are intrinsically different from the consensus structure, directly adopting view-specific subspace structures might not be a reasonable choice. In this paper, with this concern in mind, our goal is to seek novel strategies to extract valuable components from view-specific structures that are consistent with the consensus subspace structure. To this end, we propose a novel multi-view subspace clustering method named split multiplicative multi-view subspace clustering ((SMSC)-S-2) with the joint strength of a multiplicative decomposition scheme and a variable splitting scheme. Specifically, the multiplicative decomposition scheme effectively guarantees the structural consistency of the extracted components. Then, the variable splitting scheme takes a step further via extracting the structural consistent components from view-specific structures. Furthermore, an alternating optimization algorithm is proposed to optimize the resulting optimization problem, which is non-convex and constrained. We prove that this algorithm could converge to a critical point. Finally, we provide empirical studies on real-world datasets that speak to the practical efficacy of our proposed method. The source code is released on GitHub https://github.com/joshuaas/SM2SC. |
关键词 | Computational and artificial intelligence artificial intelligence learning systems unsupervised learning and computers and information processing image processing image representation |
DOI | 10.1109/TIP.2019.2913096 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2016YFB0800603] ; National Natural Science Foundation of China[61620106009] ; National Natural Science Foundation of China[U1636214] ; National Natural Science Foundation of China[61836002] ; National Natural Science Foundation of China[61672497] ; National Natural Science Foundation of China[U1605252] ; National Natural Science Foundation of China[61733007] ; National Natural Science Foundation of China[61672514] ; National Basic Research Program of China through the 973 Program[2015CB351800] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SYS013] ; Beijing Natural Science Foundation[L182057] ; Beijing Natural Science Foundation[4182079] ; Youth Innovation Promotion Association, CAS ; Shandong Provincial Natural Science Foundation[ZR2017MF001] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000482563000001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/4792 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Xu, Qianqian; Zhang, Weigang |
作者单位 | 1.Chinese Acad Sci, State Key Lab Informat Secur, Inst Informat Engn, Beijing 100093, Peoples R China 2.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 4.Harbin Inst Technol, Sch Comp Sci & Technol, Weihai 264209, Peoples R China 5.Univ Chinese Acad Sci, Chinese Acad Sci, Beijing 100049, Peoples R China 6.Cyberspace Secur Res Ctr, Peng Chong Lab, Shenzhen 518055, Peoples R China 7.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 101408, Peoples R China 8.Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing 101408, Peoples R China |
推荐引用方式 GB/T 7714 | Yang, Zhiyong,Xu, Qianqian,Zhang, Weigang,et al. Split Multiplicative Multi-View Subspace Clustering[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2019,28(10):5147-5160. |
APA | Yang, Zhiyong,Xu, Qianqian,Zhang, Weigang,Cao, Xiaochun,&Huang, Qingming.(2019).Split Multiplicative Multi-View Subspace Clustering.IEEE TRANSACTIONS ON IMAGE PROCESSING,28(10),5147-5160. |
MLA | Yang, Zhiyong,et al."Split Multiplicative Multi-View Subspace Clustering".IEEE TRANSACTIONS ON IMAGE PROCESSING 28.10(2019):5147-5160. |
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