An efficient matrix factorization based low-rank representation for subspace clustering

DOI10.1016/j.patcog.2012.06.011zbMath1248.68411OpenAlexW1992603145MaRDI QIDQ456036

J. Herrera, D. Rodríguez-Gómez

Publication date: 23 October 2012

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2012.06.011

zbMATH Keywords

matrix tri-factorizationlow rank representationalternating direction method (ADM)nuclear norm minimization (NNM)positive semidefinite (PSD)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion ⋮ Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset ⋮ Low-rank tensor completion based on log-det rank approximation and matrix factorization

Uses Software

• LMaFit
• Optspace

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