Quantile-based Random Kaczmarz for corrupted linear systems of equations

Author:

Steinerberger Stefan1

Affiliation:

1. Department of Mathematics, University of Washington, Seattle, WA 98195-4350, USA

Abstract

Abstract We consider linear systems $Ax = b$ where $A \in \mathbb{R}^{m \times n}$ consists of normalized rows, $\|a_i\|_{\ell ^2} = 1$, and where up to $\beta m$ entries of $b$ have been corrupted (possibly by arbitrarily large numbers). Haddock, Needell, Rebrova & Swartworth propose a quantile-based Random Kaczmarz method and show that for certain random matrices $A$ it converges with high likelihood to the true solution. We prove a deterministic version by constructing, for any matrix $A$, a number $\beta _A$ such that there is convergence for all perturbations with $\beta < \beta _A$. Assuming a random matrix heuristic, this proves convergence for tall Gaussian matrices with up to $\sim 0.5\%$ corruption (a number that can likely be improved).

Funder

NSF

Alfred P. Sloan Foundation

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computational Theory and Mathematics,Numerical Analysis,Statistics and Probability,Analysis

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