Globally convergent BFGS method for nonsmooth convex optimization
type: Item
instance of: scholarly article
title: Globally convergent BFGS method for nonsmooth convex optimization
zbMATH Open document ID: 0986.90076
DOI: 10.1023/A:1004633524446
author: A. I. Rauf
author: Masao Fukushima
published in: Journal of Optimization Theory and Applications
publication date: 2002-06-17T00:00:00Z
review text: For the unconstrained minimization of a nonsmooth strongly convex function \(f:\mathbb{R}^n\to \mathbb{R}\), the authors apply the BFGS method to its Moreau-Yosida regularization. The algorithm they propose makes use of approximate values of the regularized function and of its gradient; it is proved to converge to the unique optimal solution.
Mathematics Subject Classification ID: 90C53
Mathematics Subject Classification ID: 90C25
zbMATH DE Number: 1486606
zbMATH Keywords: BFGS method
zbMATH Keywords: nonsmooth convex optimization
zbMATH Keywords: Moreau-Yosida regularization
reviewed by: Juan-Enrique Martínez-Legaz
MaRDI profile type: Publication
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full work available at URL: a:1004633524446
OpenAlex ID: W1975020886
description: scientific article; zbMATH DE number 1486606