Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems

Fuente: arXiv
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Main Authors: Jin, Qinian, Liu, Yanjun
Format: Preprint
Published: 2024
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_version_ 1866913402879737856
author Jin, Qinian
Liu, Yanjun
author_facet Jin, Qinian
Liu, Yanjun
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2406_16814
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems
Jin, Qinian
Liu, Yanjun
Numerical Analysis
Optimization and Control
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.
title Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems
topic Numerical Analysis
Optimization and Control
url https://arxiv.org/abs/2406.16814