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Autores principales: Yuan, Bowen, Alkousa, Mohammad S.
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2506.01681
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author Yuan, Bowen
Alkousa, Mohammad S.
author_facet Yuan, Bowen
Alkousa, Mohammad S.
contents The part of the analysis of the convergence rate of the mirror descent method that is connected with the adaptive time-varying step size rules due to Alkousa et al. (MOTOR 2024, pp. 3-18) is corrected. Moreover, a Lipschitz-free mirror descent method that achieves weak ergodic convergence is presented, generalizing the convergence results of the mirror descent method in the absence of the Lipschitz assumption.
format Preprint
id arxiv_https___arxiv_org_abs_2506_01681
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Lipschitz-Free Mirror Descent Methods for Non-Smooth Optimization Problems
Yuan, Bowen
Alkousa, Mohammad S.
Optimization and Control
The part of the analysis of the convergence rate of the mirror descent method that is connected with the adaptive time-varying step size rules due to Alkousa et al. (MOTOR 2024, pp. 3-18) is corrected. Moreover, a Lipschitz-free mirror descent method that achieves weak ergodic convergence is presented, generalizing the convergence results of the mirror descent method in the absence of the Lipschitz assumption.
title Lipschitz-Free Mirror Descent Methods for Non-Smooth Optimization Problems
topic Optimization and Control
url https://arxiv.org/abs/2506.01681