• Corpus ID: 246240650

Stochastic asymptotical regularization for linear inverse problems

@article{Zhang2022StochasticAR,
  title={Stochastic asymptotical regularization for linear inverse problems},
  author={Ye Zhang and Chuchu Chen},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.09411}
}
We introduce Stochastic Asymptotical Regularization (SAR) methods for the uncertainty quantification of the stable approximate solution of ill-posed linear-operator equations, which are deterministic models for numerous inverse problems in science and engineering. We prove the regularizing properties of SAR with regard to meansquare convergence. We also show that SAR is an optimal-order regularization method for linear ill-posed problems provided that the terminating time of SAR is chosen… 

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