Work

Optimal Parameter Selection for the Alternating Direction Method of Multipliers (ADMM): Quadratic Problems

Year: 2014

Type: article

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.

Source: IEEE Transactions on Automatic Control

DOI: 10.1109/tac.2014.2354892

Authors: Euhanna Ghadimi, Andre Teixeira, Iman Shames, Mikael Johansson

Institutions: KTH Royal Institute of Technology, The University of Melbourne

Language: English

Topic: Advanced Optimization Algorithms Research

Subfield: Numerical Analysis

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funder: Stiftelsen för Strategisk Forskning

OpenAlex ID: W2037603831

FWCI: 31.33

Cites: 23

Cited by: 437

Related to: 10