Feb. 12, 2024, 5:43 a.m. | Zhong Zheng Shiqian Ma Lingzhou Xue

cs.LG updates on arXiv.org arxiv.org

This paper considers the robust phase retrieval problem, which can be cast as a nonsmooth and nonconvex optimization problem. We propose a new inexact proximal linear algorithm with the subproblem being solved inexactly. Our contributions are two adaptive stopping criteria for the subproblem. The convergence behavior of the proposed methods is analyzed. Through experiments on both synthetic and real datasets, we demonstrate that our methods are much more efficient than existing methods, such as the original proximal linear algorithm and …

algorithm behavior convergence cs.lg eess.sp linear math.oc optimization paper retrieval robust stat.co stat.ml

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