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Convergence Analysis of the Relaxed Proximal Point Algorithm

Min Li, Yanfei You

Abstract and Applied Analysis · 2013

doi:10.1155/2013/912846 (opens in a new tab)

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Abstract

Recently, a worst-case convergence rate was established for the Douglas-Rachford alternating direction method of multipliers (ADMM) in an ergodic sense. The relaxed proximal point algorithm (PPA) is a generalization of the original PPA which includes the Douglas-Rachford ADMM as a special case. In this paper, we provide a simple proof for the same convergence rate of the relaxed PPA in both ergodic and nonergodic senses.

Abstract licence: CC BY

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