Douglas--Rachford Splitting and ADMM for Pathological Convex Optimization
Optimization and Control
2019-09-11 v3
Abstract
Despite the vast literature on DRS and ADMM, there has been very little work analyzing their behavior under pathologies. Most analyses assume a primal solution exists, a dual solution exists, and strong duality holds. When these assumptions are not met, i.e., under pathologies, the theory often breaks down and the empirical performance may degrade significantly. In this paper, we establish that DRS only requires strong duality to work, in the sense that asymptotically iterates are approximately feasible and approximately optimal.
Keywords
Cite
@article{arxiv.1801.06618,
title = {Douglas--Rachford Splitting and ADMM for Pathological Convex Optimization},
author = {Ernest K. Ryu and Yanli Liu and Wotao Yin},
journal= {arXiv preprint arXiv:1801.06618},
year = {2019}
}
Comments
Published in Computational Optimization and Applications