A fast tri-factorization method for low-rank matrix recovery and completion

DOI10.1016/j.patcog.2012.07.003zbMath1248.68437OpenAlexW2089088255MaRDI QIDQ456030

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.2012.07.003

zbMATH Keywords

matrix completionrank minimizationnuclear norm minimizationlow-rank and sparse decompositionlow rank representation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Machine vision and scene understanding (68T45)

Related Items (8)

An inexact splitting method for the subspace segmentation from incomplete and noisy observations ⋮ Robust Manhattan non-negative matrix factorization for image recovery and representation ⋮ Robust low-rank tensor completion via new regularized model with approximate SVD ⋮ TR-STF: a fast and accurate tensor ring decomposition algorithm via defined scaled tri-factorization ⋮ An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion ⋮ Alternating direction method of multipliers for generalized low-rank tensor recovery ⋮ Robust graph regularized nonnegative matrix factorization for clustering ⋮ Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset

Uses Software

• LMaFit

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