A Nonconvex Low Rank and Sparse Constrained Multiview Subspace Clustering via $l_{\frac{1}{2}}$-Induced Tensor Nuclear Norm-Reference-Cited by-同舟云学术

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A Nonconvex Low Rank and Sparse Constrained Multiview Subspace Clustering via $l_{\frac{1}{2}}$-Induced Tensor Nuclear Norm

Published:2023 Issue: Volume:9 Page:612-625
ISSN:2373-776X
Container-title:IEEE Transactions on Signal and Information Processing over Networks
language:
Short-container-title:IEEE Trans. on Signal and Inf. Process. over Networks

Author:

Francis Jobin¹^ORCID,Madathil Baburaj²^ORCID,George Sudhish N.³^ORCID,George Sony¹^ORCID

Affiliation:

1. Department of Computer Science, Norwegian University of Science and Technology, Gjøvik, Innlandet, Norway

2. Applied Electronics & Instrumentation, Government Engineering College Kozhikode, Westhill, Kerala, India

3. Electronics & Communication Engineering, National Institute of Technology, Calicut, Kerala, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6884276/10040263/10223426.pdf?arnumber=10223426

Reference56 articles.

1. Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering

2. Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization

3. Temporal Pattern-Aware QoS Prediction via Biased Non-Negative Latent Factorization of Tensors

4. Adaptive multi-view subspace clustering for high-dimensional data

5. Dual regularized multi-view non-negative matrix factorization for clustering

Cited by 2 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. Consensus Multi-view subspace clustering based on Graph Filtering;Neurocomputing;2024-07

2. Tensor-Derived Large-Scale Multi-View Subspace Clustering With Faithful Semantics;IEEE Transactions on Signal and Information Processing over Networks;2024

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