Bi-Nuclear Tensor Schatten-<i>p</i> Norm Minimization for Multi-View Subspace Clustering-Reference-Cited by-同舟云学术

Bi-Nuclear Tensor Schatten-p Norm Minimization for Multi-View Subspace Clustering

Published:2023 Issue: Volume:32 Page:4059-4072
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Wang Shuqin¹^ORCID,Lin Zhiping²^ORCID,Cao Qi³^ORCID,Cen Yigang¹^ORCID,Chen Yongyong⁴^ORCID

Affiliation:

1. Institute of Information Sciences, and Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China

2. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Ave, Singapore

3. School of Computer Science, University of Glasgow, Robinson Rd, Singapore

4. Bio-Computing Research Center, Harbin Institute of Technology, Shenzhen, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Guangdong Natural Science Foundation

Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10183847.pdf?arnumber=10183847

Reference46 articles.

1. Essential Tensor Learning for Multi-View Spectral Clustering

2. Restricted $p$-Isometry Properties of Nonconvex Matrix Recovery

3. Low-Rank Tensor Constrained Multiview Subspace Clustering

4. Hyper-Laplacian Regularized Nonconvex Low-Rank Representation for Multi-View Subspace Clustering

5. Fast and Accurate Matrix Completion via Truncated Nuclear Norm Regularization

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