Efficiency of minimizing compositions of convex functions and smooth maps

We consider global efficiency of algorithms for minimizing a sum of a convex function and a composition of a Lipschitz convex function with a smooth map. The basic algorithm we rely on is the prox-linear method, which in each iteration solves a regularized subproblem formed by linearizing the smooth...

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Veröffentlicht in:	Mathematical programming Jg. 178; H. 1-2; S. 503 - 558
Hauptverfasser:	Drusvyatskiy, D., Paquette, C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2019 Springer Nature B.V
Schlagworte:	Algorithms Calculus of Variations and Optimal Control; Optimization Combinatorics Composition Convexity Efficiency Full Length Paper Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Theoretical Secondary 90C06 Fast gradient methods Inexactness Gauss–Newton Complexity Prox-gradient Incremental methods Primary 97N60 90C30 Composite minimization Smoothing 90C25 Acceleration
ISSN:	0025-5610, 1436-4646
Online-Zugang:	Volltext
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