Nonconvex low-rank and sparse tensor representation for multi-view subspace clustering-Reference-Cited by-同舟云学术

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Nonconvex low-rank and sparse tensor representation for multi-view subspace clustering

Published:2022-04-11 Issue:13 Volume:52 Page:14651-14664
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Wang Shuqin,Chen Yongyong,Cen Yigang^ORCID,Zhang Linna,Wang Hengyou,Voronin Viacheslav

Funder

national natural science foundation of china

natural science foundation of beijing municipality

rfbr

nsfc

national science and technology planning project

National Natural Science Foundation of China

National Key R&D Program of China

Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-03406-6.pdf

Reference53 articles.

1. Chao G, Sun S, Bi J (2021) A survey on multi-view clustering. IEEE Trans. Artif. Intell.

2. Chao G, Sun J, Lu J, Wang A-L, Langleben DD, Li C-S, Bi J (2019) Multi-view cluster analysis with incomplete data to understand treatment effects. Inf. Sci., 494

3. Vidal R, Tron R, Hartley R (2008) Multiframe motion segmentation with missing data using powerfactorization and gpca. Int. J. Comput. Vis. 79(1):85–105

4. Rao X, Tron R, Vidal R, Ma Y (2009) Motion segmentation in the presence of outlying, incomplete, or corrupted trajectories. IEEE Trans. Pattern Anal. Mach. Intell. 32(10):1832–1845

5. Wang X, Tang X (2004) A unified framework for subspace face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 26(9):1222–1228

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