Graph dual regularization non-negative matrix factorization for co-clustering

DOI10.1016/j.patcog.2011.12.015zbMath1234.68356OpenAlexW2036285176MaRDI QIDQ408044

Fanhua Shang, Fei Wang, Li-Cheng Jiao

Publication date: 28 March 2012

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2011.12.015

zbMATH Keywords

co-clusteringgraph Laplaciangraph dual regularizationlow-rank matrix factorizationnon-negative matrix factorization (NMF)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Graph theory (including graph drawing) in computer science (68R10) Pattern recognition, speech recognition (68T10)

Related Items

Orthogonal dual graph-regularized nonnegative matrix factorization for co-clustering, Detecting communities in 2-mode networks via fast nonnegative matrix trifactorization, Global discriminative-based nonnegative spectral clustering, Improving nonnegative matrix factorization with advanced graph regularization, A splitting method for the locality regularized semi-supervised subspace clustering, Dual graph-regularized sparse concept factorization for clustering, Fast semi-supervised clustering with enhanced spectral embedding, An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion, Robust graph regularized nonnegative matrix factorization for clustering, Robust bilinear factorization with missing and grossly corrupted observations, A dual reformulation and solution framework for regularized convex clustering problems, Multi-manifold matrix decomposition for data co-clustering, Multiview clustering via robust neighboring constraint nonnegative matrix factorization, Constrained dual graph regularized orthogonal nonnegative matrix tri-factorization for co-clustering, Robust sparse coding via self-paced learning for data representation

Uses Software

• JAFFE
• COIL-20
• Graclus

Cites Work

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