Nonnegative self-representation with a fixed rank constraint for subspace clustering

DOI10.1016/j.ins.2020.01.014zbMath1462.62398OpenAlexW3000268651MaRDI QIDQ2662714

Guo Zhong, Chi-Man Pun

Publication date: 14 April 2021

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

Full work available at URL: https://doi.org/10.1016/j.ins.2020.01.014

zbMATH Keywords

least squares regressiongraph clusteringsubspace clusteringnonnegative representation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Probabilistic graphical models (62H22)

Related Items (3)

Beyond linear subspace clustering: a comparative study of nonlinear manifold clustering algorithms ⋮ Simultaneous multi-graph learning and clustering for multiview data ⋮ Adaptive graph learning for semi-supervised feature selection with redundancy minimization

Uses Software

• UCI-ml
• JAFFE
• GeneSrF

Cites Work

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• A manifold learning approach to dimensionality reduction for modeling data
• Robust principal component analysis?
• Enhancing Low-Rank Subspace Clustering by Manifold Regularization
• Low-Rank Matrix Factorization With Adaptive Graph Regularizer
• Subspace Clustering via Learning an Adaptive Low-Rank Graph
• Correntropy-Induced Robust Low-Rank Hypergraph

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