Parallel random block-coordinate forward–backward algorithm: a unified convergence analysis

We study the block-coordinate forward–backward algorithm in which the blocks are updated in a random and possibly parallel manner, according to arbitrary probabilities. The algorithm allows different stepsizes along the block-coordinates to fully exploit the smoothness properties of the objective fu...

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Veröffentlicht in:	Mathematical programming Jg. 193; H. 1; S. 225 - 269
Hauptverfasser:	Salzo, Saverio, Villa, Silvia
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2022 Springer Springer Nature B.V
Schlagworte:	Algorithms Analysis Calculus of Variations and Optimal Control; Optimization Combinatorics Convergence Convexity Error analysis Full Length Paper Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Smoothness Theoretical Random block-coordinate descent 65K05 Convex optimization 90C25 Convergence rates Error bounds 90C06 49M27 Arbitrary sampling Stochastic quasi-Fejér sequences Parallel algorithms Forward–backward algorithm
ISSN:	0025-5610, 1436-4646
Online-Zugang:	Volltext
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