Optimal parameter selection for the alternating direction method of multipliers (ADMM): quadratic problems
Optimization and Control
2016-11-17 v2 Dynamical Systems
Abstract
The alternating direction method of multipliers (ADMM) has emerged as a powerful technique for large-scale structured optimization. Despite many recent results on the convergence properties of ADMM, a quantitative characterization of the impact of the algorithm parameters on the convergence times of the method is still lacking. In this paper we find the optimal algorithm parameters that minimize the convergence factor of the ADMM iterates in the context of l2-regularized minimization and constrained quadratic programming. Numerical examples show that our parameter selection rules significantly outperform existing alternatives in the literature.
Keywords
Cite
@article{arxiv.1306.2454,
title = {Optimal parameter selection for the alternating direction method of multipliers (ADMM): quadratic problems},
author = {Euhanna Ghadimi and André Teixeira and Iman Shames and Mikael Johansson},
journal= {arXiv preprint arXiv:1306.2454},
year = {2016}
}
Comments
Submitted to IEEE Transactions on Automatic Control