The multiproximal linearization method for convex composite problems

Composite minimization involves a collection of smooth functions which are aggregated in a nonsmooth manner. In the convex setting, we design an algorithm by linearizing each smooth component in accordance with its main curvature. The resulting method, called the Multiprox method, consists in solvin...

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Bibliographic Details
Published in:	Mathematical programming Vol. 182; no. 1-2; pp. 1 - 36
Main Authors:	Bolte, Jérôme, Chen, Zheng, Pauwels, Edouard
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2020 Springer Nature B.V Springer Verlag
Subjects:	Algorithms Approximation Calculus of Variations and Optimal Control; Optimization Combinatorics Complexity Constraints Curvature Full Length Paper Mathematical and Computational Physics Mathematical Methods in Physics Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Methods Numerical Analysis Operators (mathematics) Optimization Optimization and Control Theoretical 90C30 Convex optimization 90C25 90C47 Composite optimization First order methods Proximal Gauss–Newton’s method Prox-linear method Complexity
ISSN:	0025-5610, 1436-4646
Online Access:	Get full text
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