Inexact Proximal Point Algorithms and Descent Methods in Optimization

被引：0
作者：
Carlos Humes
Paulo J. S. Silva
机构：
[1] University of São Paulo,Department of Computer Science
来源：
Optimization and Engineering | 2005年 / 6卷
关键词：
proximal methods; convex programming; monotone operators;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Proximal point methods have been used by the optimization community to analyze different algorithms like multiplier methods for constrained optimization, and bundle methods for nonsmooth problems. This paper aims to be an introduction to the theory of proximal algorithms borrowing ideas from descent methods for unconstrained optimization. This new viewpoint allows us to present a simple and natural convergence proof. We also improve slightly the results from Solodov and Svaiter (1999).
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页码：257 / 271
页数：14
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