Surrounding the solution of a Linear System of Equations from all sides

Abstract

Suppose A ∈ Rn × n is invertible and we are looking for the solution of Ax = b. Given an initial guess x1 ∈ R, we show that by reflecting through hyperplanes generated by the rows of A, we can generate an infinite sequence (xk)k=1∞ such that all elements have the same distance to the solution, i.e. \|xk - x\| = \|x1 - x\|. If the hyperplanes are chosen at random, averages over the sequence converge and E \| x - 1m Σk=1m xk \| ≤ 1 + \|A\|F \|A-1\|m ·\|x-x1\|. The bound does not depend on the dimension of the matrix. This introduces a purely geometric way of attacking the problem: are there fast ways of estimating the location of the center of a sphere from knowing many points on the sphere? Our convergence rate (coinciding with that of the Random Kaczmarz method) comes from averaging, can one do better?

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