An inexact LQP alternating direction method for solving a class of structured variational inequalities

Authors:
Abdellah Bnouhachem;M. H. Xu
Affiliations:
-;-
Venue:
Computers & Mathematics with Applications
Year:
2014

Citing 7
Cited 0

On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators

Mathematical Programming: Series A and B
A proximal-based decomposition method for convex minimization problems

Mathematical Programming: Series A and B
A variable-penalty alternating directions method for convex optimization

Mathematical Programming: Series A and B
A Logarithmic-Quadratic Proximal Method for Variational Inequalities

Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part I
Convergence of Proximal-Like Algorithms

SIAM Journal on Optimization
Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing

SIAM Journal on Scientific Computing
An LQP-Based Decomposition Method for Solving a Class of Variational Inequalities

SIAM Journal on Optimization

Quantified Score

Hi-index	0.09

Visualization

Abstract

In this paper, we present an inexact alternating direction method. Each iteration of the proposed method contains a prediction and a correction, the predictor is obtained via solving the logarithmic-quadratic proximal (LQP) system approximately under significantly relaxed accuracy criterion and the new iterate is computed directly by an explicit formula derived from the original LQP method. Under certain conditions, the global convergence of the proposed method is proved.