Self-regularized fixed-rank representation for subspace segmentation

DOI10.1016/J.INS.2017.05.007zbMath1435.68333OpenAlexW2612568300MaRDI QIDQ778387

D. Kharzeev

Publication date: 2 July 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2017.05.007

zbMATH Keywords

low-rank representationsubspace segmentationfixed-rank representationstructure constraint

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Machine vision and scene understanding (68T45)

Uses Software

• AR face

Cites Work

• Generalized transfer subspace learning through low-rank constraint
• On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
• Solution of the matrix equation AX - XB = C
• Hybrid linear modeling via local best-fit flats
• A Singular Value Thresholding Algorithm for Matrix Completion
• Estimation of Subspace Arrangements with Applications in Modeling and Segmenting Mixed Data
• Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

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