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- W3008521353 abstract "In this paper, we apply randomized algorithms to approximate the total least squares (TLS) solution of the problem Ax≈b in the large-scale discrete ill-posed problems. A regularization technique, based on the multiplicative randomization and the subspace iteration, is proposed to obtain the approximate core problem. In the error analysis, we provide upper bounds for the errors of the solution and the residual of the randomized core reduction. Illustrative numerical examples and comparisons are presented." @default.
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- W3008521353 date "2020-09-01" @default.
- W3008521353 modified "2023-10-14" @default.
- W3008521353 title "Randomized core reduction for discrete ill-posed problem" @default.
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- W3008521353 doi "https://doi.org/10.1016/j.cam.2020.112797" @default.
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