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arXiv · 2002.12670

An inertial alternating direction method of multipliers for solving a two-block separable convex minimization problem

Yang Yang·Yuchao Tang
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Abstract

The alternating direction method of multipliers (ADMM) is a widely used method for solving many convex minimization models arising in signal and image processing. In this paper, we propose an inertial ADMM for solving a two-block separable convex minimization problem with linear equality constraints. This algorithm is obtained by making use of the inertial Douglas-Rachford splitting algorithm to the corresponding dual of the primal problem. We study the convergence analysis of the proposed algorithm in infinite-dimensional Hilbert spaces. Furthermore, we apply the proposed algorithm on the robust principal component pursuit problem and also compare it with other state-of-the-art algorithms. Numerical results demonstrate the advantage of the proposed algorithm.

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Yang Yang, Yuchao Tang. 2020-02-28. An inertial alternating direction method of multipliers for solving a two-block separable convex minimization problem. https://doi.org/10.3770/j.issn%3A2095-2651.2021.02.008

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