Approximation accuracy, gradient methods, and error bound for structured convex optimization

Mathematical Programming

Volumn 125, Issue 2, 2010, Pages 263-295

  Tseng, Paul ^a  

^a NONE

Author keywords

Approximation accuracy; Compressed sensing; Convex optimization; Error bound; L1 regularization; Linear convergence; Nuclear trace norm; Proximal gradient method; Regression; Sensor network localization; Variable selection

Indexed keywords

APPROXIMATION ACCURACY; COMPRESSED SENSING; ERROR BOUND; L1-REGULARIZATION; LINEAR CONVERGENCE; NUCLEAR/TRACE NORM; PROXIMAL GRADIENT METHOD; REGRESSION; SENSOR NETWORK LOCALIZATION; VARIABLE SELECTION;

GRADIENT METHODS; IMAGE PROCESSING; OPTIMIZATION; PROBLEM SOLVING; REGRESSION ANALYSIS; SENSOR NETWORKS; SIGNAL RECONSTRUCTION;

CONVEX OPTIMIZATION;

EID: 77958113563     PISSN: 00255610     EISSN: 14364646     Source Type: Journal    
DOI: 10.1007/s10107-010-0394-2     Document Type: Conference Paper

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