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CDIMC-net: Cognitive deep incomplete multi-view clustering network
Wen,Jie1,2; Zhang,Zheng1,2,3; Xu,Yong1,2,3; Zhang,Bob4; Fei,Lunke5; Xie,Guo Sen6
2021-01
Conference Name29th International Joint Conference on Artificial Intelligence
Source PublicationIJCAI International Joint Conference on Artificial Intelligence
Volume2021-January
Pages3230-3236
Conference Date1 January 2021 - null
Conference PlaceIJCAI 2020
Abstract

In recent years, incomplete multi-view clustering, which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Although a series of methods have been proposed to address this issue, the following problems still exist: 1) Almost all of the existing methods are based on shallow models, which is difficult to obtain discriminative common representations. 2) These methods are generally sensitive to noise or outliers since the negative samples are treated equally as the important samples. In this paper, we propose a novel incomplete multi-view clustering network, called Cognitive Deep Incomplete Multi-view Clustering Network (CDIMC-net), to address these issues. Specifically, it captures the high-level features and local structure of each view by incorporating the view-specific deep encoders and graph embedding strategy into a framework. Moreover, based on the human cognition, i.e., learning from easy to hard, it introduces a self-paced strategy to select the most confident samples for model training, which can reduce the negative influence of outliers. Experimental results on several incomplete datasets show that CDIMC-net outperforms the state-of-the-art incomplete multi-view clustering methods.

URLView the original
Language英語English
Scopus ID2-s2.0-85097330019
Fulltext Access
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Bio-Computing Research Center,Harbin Institute of Technology,Shenzhen, Shenzhen,China
2.Shenzhen Key Laboratory of Visual Object Detection and Recognition,Shenzhen,China
3.Pengcheng Laboratory,Shenzhen,China
4.Department of Computer and Information Science,University of Macau,Taipa,Macao
5.School of Computer Science and Technology,Guangdong University of Technology,Guangzhou,China
6.Inception Institute of Artificial Intelligence,Abu Dhabi,United Arab Emirates
Recommended Citation
GB/T 7714
Wen,Jie,Zhang,Zheng,Xu,Yong,et al. CDIMC-net: Cognitive deep incomplete multi-view clustering network[C],2021:3230-3236.
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