Semisupervised Progressive Representation Learning for Deep Multiview Clustering

doi:10.1109/TNNLS.2023.3278379

	Semisupervised Progressive Representation Learning for Deep Multiview Clustering
	Chen, Rui1,2 ; Tang, Yongqiang2 ; Xie, Yuan3 ; Feng, Wenlong 1,4; Zhang, Wensheng1,2
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
	2023-05-31
页码	15
通讯作者	Tang, Yongqiang(yongqiang.tang@ia.ac.cn)
摘要	Multiview clustering has become a research hotspot in recent years due to its excellent capability of heterogeneous data fusion. Although a great deal of related works has appeared one after another, most of them generally overlook the potentials of prior knowledge utilization and progressive sample learning, resulting in unsatisfactory clustering performance in real-world applications. To deal with the aforementioned drawbacks, in this article, we propose a semisupervised progressive representation learning approach for deep multiview clustering (namely, SPDMC). Specifically, to make full use of the discriminative information contained in prior knowledge, we design a flexible and unified regularization, which models the sample pairwise relationship by enforcing the learned view-specific representation of must-link (ML) samples (cannot-link (CL) samples) to be similar (dissimilar) with cosine similarity. Moreover, we introduce the self-paced learning (SPL) paradigm and take good care of two characteristics in terms of both complexity and diversity when progressively learning multiview representations, such that the complementarity across multiple views can be squeezed thoroughly. Through comprehensive experiments on eight widely used image datasets, we prove that the proposed approach can perform better than the state-of-the-art opponents.
关键词	Representation learning Training Data models Task analysis Complexity theory Semisupervised learning Optimization Deep clustering multiview clustering progressive sample learning semisupervised learning
DOI	10.1109/TNNLS.2023.3278379
关键词[WOS]	SELF-REPRESENTATION ; IMAGE FEATURES ; SCALE
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2021ZD0111000] ; National Natural Science Foundation of China[62106266] ; National Natural Science Foundation of China[U22B2048] ; National Natural Science Foundation of China[62173328] ; National Natural Science Foundation of China[61976213] ; National Natural Science Foundation of China[62222602] ; Natural Science Foundation of Shanghai[20ZR1417700]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Shanghai
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:001005792700001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53466
专题	多模态人工智能系统全国重点实验室
通讯作者	Tang, Yongqiang
作者单位	1.Hainan Univ, Coll Informat Sci & Technol, Haikou 570208, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 3.East China Normal Univ, Sch Comp Sci & Technol, Shanghai 200241, Peoples R China 4.Hainan Univ, State Key Lab Marine Resource Utilizat South China, Haikou 570208, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Chen, Rui,Tang, Yongqiang,Xie, Yuan,et al. Semisupervised Progressive Representation Learning for Deep Multiview Clustering[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2023:15.
APA	Chen, Rui,Tang, Yongqiang,Xie, Yuan,Feng, Wenlong,&Zhang, Wensheng.(2023).Semisupervised Progressive Representation Learning for Deep Multiview Clustering.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,15.
MLA	Chen, Rui,et al."Semisupervised Progressive Representation Learning for Deep Multiview Clustering".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023):15.