Weighted iteration complexity of the sPADMM on the KKT residuals for convex composite optimization
Optimization and Control
2016-11-11 v1
Abstract
In this paper we establish an weighted iteration complexity on the KKT residuals yielded by the sPADMM (semi-proximal alternating direction method of multiplier) for the convex composite optimization problem. This result, which is derived with the help of a novel generalized HPE (hybrid proximal extra-gradient) iteration formula, first fills the gap on the ergodic iteration complexity of the classic ADMM with a large step-size and its many proximal variants.
Keywords
Cite
@article{arxiv.1611.03167,
title = {Weighted iteration complexity of the sPADMM on the KKT residuals for convex composite optimization},
author = {Li Shen and Shaohua Pan},
journal= {arXiv preprint arXiv:1611.03167},
year = {2016}
}