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math.NA2018★ 1 cited
Uncertainty quantification in large Bayesian linear inverse problems using Krylov subspace methods
Arvind K. Saibaba, Julianne Chung, Katrina Petroske
For linear inverse problems with a large number of unknown parameters, uncertainty quantification remains a challenging task. In this work, we use Krylov subspace methods to approx…
math.NA2018
Randomized subspace iteration: Analysis of canonical angles and unitarily invariant norms
Arvind K. Saibaba
This paper is concerned with the analysis of the randomized subspace iteration for the computation of low-rank approximations. We present three different kinds of bounds. First, we…