An implementable proximal point algorithmic framework for nuclear norm minimization

Mathematical Programming

Volumn 133, Issue 1-2, 2012, Pages 399-436

  Liu, Yong Jin ^a   Sun, Defeng ^b   Toh, Kim Chuan ^b,c  

^a SHENYANG AEROSPACE UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c SINGAPORE MIT ALLIANCE   (Singapore)

Author keywords

Accelerated proximal gradient method; Gradient projection method; Nuclear norm minimization; Proximal point method; Rank minimization

Indexed keywords

ALGORITHMIC FRAMEWORK; CONVERGENCE RESULTS; CONVEX RELAXATION; EFFICIENT IMPLEMENTATION; GRADIENT PROJECTION METHODS; LINEAR EQUALITY; MATRIX COMPLETION PROBLEMS; MINIMIZATION PROBLEMS; NOISY DATA; NUMERICAL RESULTS; PRIMAL-DUAL; PROXIMAL POINT ALGORITHM; PROXIMAL POINT METHOD; PROXIMAL POINTS; REAL MATRICES; SECOND ORDER CONE; STATE-OF-THE-ART ALGORITHMS; SUB-PROBLEMS;

GRADIENT METHODS; MATRIX ALGEBRA; RELAXATION PROCESSES;

ALGORITHMS;

EID: 84862272060     PISSN: 00255610     EISSN: 14364646     Source Type: Journal    
DOI: 10.1007/s10107-010-0437-8     Document Type: Article

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