Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems
Numerical Analysis
2024-06-25 v1 Numerical Analysis
Optimization and Control
Abstract
In this paper we consider a stochastic heavy-ball method for solving linear ill-posed inverse problems. With suitable choices of the step-sizes and the momentum coefficients, we establish the regularization property of the method under {\it a priori} selection of the stopping index and derive the rate of convergence under a benchmark source condition on the sought solution. Numerical results are provided to test the performance of the method.
Cite
@article{arxiv.2406.16814,
title = {Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems},
author = {Qinian Jin and Yanjun Liu},
journal= {arXiv preprint arXiv:2406.16814},
year = {2024}
}