Quantitative results on a Halpern-type proximal point algorithm
Optimization and Control
2021-03-01 v4 Logic
Abstract
We apply proof mining methods to analyse a result of Boikanyo and Moro\c{s}anu on the strong convergence of a Halpern-type proximal point algorithm. As a consequence, we obtain quantitative versions of this result, providing uniform effective rates of asymptotic regularity and metastability.
Cite
@article{arxiv.2001.10040,
title = {Quantitative results on a Halpern-type proximal point algorithm},
author = {Laurentiu Leustean and Pedro Pinto},
journal= {arXiv preprint arXiv:2001.10040},
year = {2021}
}
Comments
This is a preprint of an article published in Computational Optimization and Applications. The final authenticated version is available online at: https://doi.org/10.1007/s10589-021-00263-w