Self-paced and auto-weighted multi-view clustering-Reference-Cited by-同舟云学术

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Self-paced and auto-weighted multi-view clustering

Published:2020-03 Issue: Volume:383 Page:248-256
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Ren Yazhou^ORCID,Huang Shudong,Zhao Peng,Han Minghao,Xu Zenglin^ORCID

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

UESTC

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference64 articles.

1. Multi-view clustering;Bickel,2004

2. Spectral clustering with two views;De Sa,2005

3. Non-redundant multi-view clustering via orthogonalization;Cui,2007

4. Co-clustering of multi-view datasets: a parallelizable approach;Bisson,2012

5. Correlational spectral clustering;Blaschko,2008

Cited by 40 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Co-regularized optimal high-order graph embedding for multi-view clustering;Pattern Recognition;2025-01

2. A novel federated multi-view clustering method for unaligned and incomplete data fusion;Information Fusion;2024-08

3. Self-paced regularized adaptive multi-view unsupervised feature selection;Neural Networks;2024-07

4. View-Driven Multi-View Clustering via Contrastive Double-Learning;Entropy;2024-05-29

5. Structure-guided feature and cluster contrastive learning for multi-view clustering;Neurocomputing;2024-05

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