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

2024/06/24 by Qinian Jin, Jin, Qinian, Yan‐Jun Liu +1
Engineering · Mathematics · #FOS: Mathematics #Numerical Analysis (math.NA) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Statistical and numerical algorithms

paper · pdf · doi:10.48550/arxiv.2406.16814

openalex publication_date 2024/06/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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