2016/06/07 by Jingwei Liang, Liang, Jingwei, Jalal Fadili +3 · 2 citations
Computer Science · Mathematics · #Advanced Optimization Algorithms Research #Approximation Theory and Sequence Spaces #FOS: Mathematics #Optimization and Control (math.OC) #Optimization and Variational Analysis
paper · pdf · doi:10.48550/arxiv.1606.02116
openalex publication_date 2016/06/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Douglas--Rachford (DR) and alternating direction method of multipliers (ADMM) are two proximal splitting algorithms designed to minimize the sum of two proper lower semi-continuous convex functions whose proximity operators are easy to compute. The goal of this work is to understand the local linear convergence behaviour of DR/ADMM when the involved functions are moreover partly smooth. More precisely, when the two functions are partly smooth relative to their respective smooth submanifolds, we show that DR/ADMM (i) identifies these manifolds in finite time; (ii) enters a local linear convergence regime. When both functions are locally polyhedral, we show that the optimal convergence radius is given in terms of the cosine of the Friedrichs angle between the tangent spaces of the identified submanifolds. Under polyhedrality of both functions, we also provide condition sufficient for finite convergence of DR. The obtained results are illustrated by several concrete examples and supported by numerical experiments.