Line Search and Trust-Region Methods for Convex-Composite Optimization

2018/06/13 by Burke, James V., Engle, Abraham
#FOS: Mathematics #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.1806.05218

Abstract

We consider descent methods for solving non-finite valued nonsmooth convex-composite optimization problems that employ Gauss-Newton subproblems to determine the iteration update. Specifically, we establish the global convergence properties for descent methods that use a backtracking line search, a weak Wolfe line search, or a trust-region update. All of these approaches are designed to exploit the structure associated with convex-composite problems.

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