Robust multi-view graph clustering in latent energy-preserving embedding space

DOI10.1016/J.INS.2021.05.025OpenAlexW3159989163MaRDI QIDQ6071258

Zhen Huang, Zhenwen Ren, Mithun Mukherjee, Quan-Sen Sun, Xingfeng Li, Yuqing Huang

Publication date: 23 November 2023

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2021.05.025

zbMATH Keywords

clusteringnoise removalenergy-preservingmulti-view learninggraph learning

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Auto-weighted multi-view co-clustering with bipartite graphs
• Learning robust affinity graph representation for multi-view clustering
• Robust low-rank kernel multi-view subspace clustering based on the Schatten \(p\)-norm and correntropy
• Deep low-rank subspace ensemble for multi-view clustering
• Joint correntropy metric weighting and block diagonal regularizer for robust multiple kernel subspace clustering
• Flexible Multi-View Dimensionality Co-Reduction
• Learning Latent Low-Rank and Sparse Embedding for Robust Image Feature Extraction

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