Analysis of the gradient method with an Armijo-Wolfe line search on a class of non-smooth convex functions

被引:11
作者
Asl, Azam [1 ]
Overton, Michael L. [1 ]
机构
[1] NYU, Courant Inst Math Sci, New York, NY 10012 USA
基金
美国国家科学基金会;
关键词
Steepest descent method; convex optimization; non-smooth optimization; SAMPLING ALGORITHM; MINIMIZATION; CONVERGENCE; NONCONVEX;
D O I
10.1080/10556788.2019.1673388
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
It has long been known that the gradient (steepest descent) method may fail on non-smooth problems, but the examples that have appeared in the literature are either devised specifically to defeat a gradient or subgradient method with an exact line search or are unstable with respect to perturbation of the initial point. We give an analysis of the gradient method with steplengths satisfying the Armijo and Wolfe inexact line search conditions on the non-smooth convex function . We show that if a is sufficiently large, satisfying a condition that depends only on the Armijo parameter, then, when the method is initiated at any point with , the iterates converge to a point with , although f is unbounded below. We also give conditions under which the iterates , using a specific Armijo-Wolfe bracketing line search. Our experimental results demonstrate that our analysis is reasonably tight.
引用
收藏
页码:223 / 242
页数:20
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