Proximal Algorithms for a class of abstract convex functions
Optimization and Control
2024-02-29 v2
Abstract
In this paper we analyze a class of nonconvex optimization problem from the viewpoint of abstract convexity. Using the respective generalizations of the subgradient we propose an abstract notion proximal operator and derive a number of algorithms, namely an abstract proximal point method, an abstract forward-backward method and an abstract projected subgradient method. Global convergence results for all algorithms are discussed and numerical examples are given
Cite
@article{arxiv.2402.17072,
title = {Proximal Algorithms for a class of abstract convex functions},
author = {Ewa Bednarczuk and Dirk Lorenz and The Hung Tran},
journal= {arXiv preprint arXiv:2402.17072},
year = {2024}
}