A Framework for Regularization via Operator Approximation

@article{Chung2015AFF,
  title={A Framework for Regularization via Operator Approximation},
  author={Julianne Chung and Misha Elena Kilmer and Dianne P. O’Leary},
  journal={SIAM J. Sci. Comput.},
  year={2015},
  volume={37}
}
Regularization approaches based on spectral filtering can be highly effective in solving ill-posed inverse problems. These methods, however, require computing the singular value decomposition (SVD) and choosing appropriate regularization parameters. These tasks can be prohibitively expensive for large-scale problems. In this paper, we present a framework that uses operator approximations to efficiently obtain good regularization parameters without an SVD of the original operator. Instead, we… 

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