Semisupervised Progressive Representation Learning for Deep Multiview Clustering
文献类型：期刊论文
| 作者 | Chen, Rui1,4 ; Tang, Yongqiang4; Xie, Yuan3; Feng, Wenlong1,2; Zhang, Wensheng1,4
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| 刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
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| 出版日期 | 2023-05-31 |
| 页码 | 15 |
| ISSN号 | 2162-237X |
| 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 |
| 通讯作者 | Tang, Yongqiang(yongqiang.tang@ia.ac.cn) |
| 英文摘要 | 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. |
| WOS关键词 | SELF-REPRESENTATION ; IMAGE FEATURES ; SCALE |
| 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] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:001005792700001 |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Shanghai |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53465]  |
| 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.Hainan Univ, State Key Lab Marine Resource Utilizat South China, Haikou 570208, Peoples R China 3.East China Normal Univ, Sch Comp Sci & Technol, Shanghai 200241, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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