Multi-view clustering based on graph-regularized nonnegative matrix factorization for object recognition

DOI10.1016/j.ins.2017.11.038zbMath1436.68323OpenAlexW2770558925MaRDI QIDQ781931

Xinyu Zhang, Jianghao Huo, Li Zheng, Yuchao Liu, Hongbo Gao, Jianhui Zhao, Guopeng Li, Jialun Yin

Publication date: 20 July 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2017.11.038

zbMATH Keywords

clusteringnonnegative matrix factorizationgraph regularizationmulti-vieworthogonal constraint

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Factorization of matrices (15A23) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (13)

Multiple kernel low-rank representation-based robust multi-view subspace clustering ⋮ Multiview clustering via exclusive non-negative subspace learning and constraint propagation ⋮ Low-rank nonnegative matrix factorization on Stiefel manifold ⋮ Joint specific and correlated information exploration for multi-view action clustering ⋮ Mutual structure learning for multiple kernel clustering ⋮ Dual semi-supervised convex nonnegative matrix factorization for data representation ⋮ Fast unsupervised embedding learning with anchor-based graph ⋮ 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 ⋮ Beyond global fusion: a group-aware fusion approach for multi-view image clustering ⋮ Low-rank local tangent space embedding for subspace clustering ⋮ Auto-weighted multi-view co-clustering with bipartite graphs ⋮ Semi-paired multiview clustering based on nonnegative matrix factorization

Uses Software

• SymNMF

Cites Work

• Unnamed Item
• SymNMF: nonnegative low-rank approximation of a similarity matrix for graph clustering
• SVD based initialization: A head start for nonnegative matrix factorization
• Constrained Multi-View Video Face Clustering
• Learning the parts of objects by non-negative matrix factorization

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