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This paper considers the robust phase retrieval problem, which can be cast asa nonsmooth and nonconvex optimization problem. We propose a new inexactproximal linear algorithm with the subproblem being solved inexactly. Ourcontributions are two adaptive stopping criteria for the subproblem. Theconvergence behavior of the proposed methods is analyzed. Through experimentson both synthetic and real datasets, we demonstrate that our methods are muchmore efficient than existing methods, such as the original proximal linearalgorithm and the subgradient method.

A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval