用于具有惯性效应的凸优化的相对误差不精确 ADMM 分裂算法

arXiv - MATH - Optimization and Control Pub Date : 2024-09-16 DOI:arxiv-2409.10311

M. Marques Alves, M. Geremia

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引用次数: 0

摘要

我们提出了一种用于凸优化的新的相对误差不精确交替乘法（ADMM）。我们证明了主算法的渐近收敛性以及残差的点和遍历迭代复杂性。我们还通过一些回归问题的初步数值实验证明了所提算法的有效性。

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A relative-error inexact ADMM splitting algorithm for convex optimization with inertial effects

We propose a new relative-error inexact version of the alternating direction method of multipliers (ADMM) for convex optimization. We prove the asymptotic convergence of our main algorithm as well as pointwise and ergodic iteration-complexities for residuals. We also justify the effectiveness of the proposed algorithm through some preliminary numerical experiments on regression problems.

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arXiv - MATH - Optimization and Control

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