Journal:Neurocomputing

Key Words:Multi-view clustering; Incomplete views; Deep semantic mapping; Graph regularization

Abstract:Multi-view clustering, which explores complementary information between multiple feature sets by consensus grouping, has benefited many data analytic applications. The majority of previous multi-view clustering studies usually assume that all feature sets appear in complete. In real-world applications, however, it is often the case that some views could suffer from the missing of examples, resulting in incomplete feature sets. The incompleteness of views makes it difficult to synthesize all feature sets and achieve a comprehensive description of data samples. In this paper, we develop a novel

Co-author:Chen, Zhikui,Jane Wang, Z,Leung, Victor C.M

First Author:Zhao, Liang

Indexed by:Development research

Correspondence Author:Cissy Yang

Document Code:000418370200101

First-Level Discipline:Control Science and Engineering

Document Type:J

Volume:275

Page Number:1053-1062

ISSN No.:09252312

Translation or Not:no

CN No.:null

Date of Publication:2018-01-31

Included Journals:SCI

Links to published journals:https://doi-org-443.e.buaa.edu.cn/10.1016/j.neucom.2017.07.016

Attachments: