A Fast solver for high condition linear systems using randomized stable solutions of its blocks
Abstract
We present an enhanced version of the row-based randomized block-Kaczmarz method to solve a linear system of equations. This improvement makes use of a regularization during block updates in the solution, and a dynamic proposal distribution based on the current residue and effective orthogonality between blocks. This improved method provides significant gains in solving high-condition number linear systems that are either sparse, or dense least-squares problems that are significantly over/under determined. Considering the poor generalizability of preconditioners for such problems, it can also serve as a pre-solver for other iterative numerical methods when required, and as an inner iteration in certain types of GMRES solvers for linear systems.
Cite
@article{arxiv.2510.02156,
title = {A Fast solver for high condition linear systems using randomized stable solutions of its blocks},
author = {Suvendu Kar and Murugesan Venkatapathi},
journal= {arXiv preprint arXiv:2510.02156},
year = {2025}
}