Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems
<|reference_start|>Convergence analysis of a stochastic heavy-ball method for linear ill-posed problems: 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.<|reference_end|>
@article{jin2024convergence,
    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},
    archivePrefix={arXiv},
    eprint={2406.16814},
    primaryClass={math.NA cs.NA math.OC}
}