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Tight Linear Convergence Rate Bounds for Douglas-Rachford Splitting and\n ADMM

2015/03/03 by Pontus Giselsson, Giselsson, Pontus
Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Direction-of-Arrival Estimation Techniques #Advanced MIMO Systems Optimization

paper · pdf · doi:10.48550/arxiv.1503.00887

Abstract

Douglas-Rachford splitting and the alternating direction method of\nmultipliers (ADMM) can be used to solve convex optimization problems that\nconsist of a sum of two functions. Convergence rate estimates for these\nalgorithms have received much attention lately. In particular, linear\nconvergence rates have been shown by several authors under various assumptions.\nOne such set of assumptions is strong convexity and smoothness of one of the\nfunctions in the minimization problem. The authors recently provided a linear\nconvergence rate bound for such problems. In this paper, we show that this rate\nbound is tight for many algorithm parameter choices.\n

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