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Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive stepsizes and convergence

Dirk A. Lorenz(d.lorenz***at***tu-braunschweig.de)
Quoc Tran-Dinh(quoctd***at***email.unc.edu)

Abstract: We revisit the classical Douglas-Rachford (DR) method for finding a zero of the sum of two maximal monotone operators. Since the practical performance of the DR method crucially depends on the stepsizes, we aim at developing an adaptive stepsize rule. To that end, we take a closer look at a linear case of the problem and use our findings to develop a stepsize strategy that eliminates the need for stepsize tuning. We analyze a general non-stationary DR scheme and prove its convergence for a convergent sequence of stepsizes with summable increments. This, in turn, proves the convergence of the method with the new adaptive stepsize rule. We also derive the related non-stationary alternating direction method of multipliers (ADMM) from such a non-stationary DR method. We illustrate the efficiency of the proposed methods on several numerical examples.

Keywords: Douglas-Rachford method, alternating direction methods of multipliers, maximal monotone inclusions, adaptive stepsize, non-stationary iteration

Category 1: Convex and Nonsmooth Optimization (Convex Optimization )


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Entry Submitted: 01/18/2018
Entry Accepted: 01/18/2018
Entry Last Modified: 01/18/2018

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