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Main Authors: Themelis, Andreas, Hermans, Ben, Patrinos, Panagiotis
Format: Preprint
Published: 2020
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Online Access:https://arxiv.org/abs/2004.00083
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author Themelis, Andreas
Hermans, Ben
Patrinos, Panagiotis
author_facet Themelis, Andreas
Hermans, Ben
Patrinos, Panagiotis
contents Difference-of-convex (DC) optimization problems are shown to be equivalent to the minimization of a Lipschitz-differentiable "envelope". A gradient method on this surrogate function yields a novel (sub)gradient-free proximal algorithm which is inherently parallelizable and can handle fully nonsmooth formulations. Newton-type methods such as L-BFGS are directly applicable with a classical linesearch. Our analysis reveals a deep kinship between the novel DC envelope and the forward-backward envelope, the former being a smooth and convexity-preserving nonlinear reparametrization of the latter.
format Preprint
id arxiv_https___arxiv_org_abs_2004_00083
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle A new envelope function for nonsmooth DC optimization
Themelis, Andreas
Hermans, Ben
Patrinos, Panagiotis
Optimization and Control
90C26, 90C53, 90C06
Difference-of-convex (DC) optimization problems are shown to be equivalent to the minimization of a Lipschitz-differentiable "envelope". A gradient method on this surrogate function yields a novel (sub)gradient-free proximal algorithm which is inherently parallelizable and can handle fully nonsmooth formulations. Newton-type methods such as L-BFGS are directly applicable with a classical linesearch. Our analysis reveals a deep kinship between the novel DC envelope and the forward-backward envelope, the former being a smooth and convexity-preserving nonlinear reparametrization of the latter.
title A new envelope function for nonsmooth DC optimization
topic Optimization and Control
90C26, 90C53, 90C06
url https://arxiv.org/abs/2004.00083