This paper proposes a distributed-memory parallel randomized iterative algorithm for solving linear systems, called the parallel randomized kaczmarz projection (PRKP) algorithm. The algorithm has the property of greedy sampling, alternating projection, and lazy approximation.
Abstract: This paper proposes a distributed-memory parallel randomized iterative algorithm for solving linear systems, called the parallel randomized ...
Abstract—This paper proposes a distributed-memory parallel randomized iterative algorithm for solving linear systems, called.
TL;DR: This work combines two iterative algorithms for solving large-scale systems of linear inequalities, the relaxation method of Agmon, Motzkin et al. and ...
We develop a novel, fundamental, and surprisingly simple randomized iterative method for solving consistent linear systems. Our method has six different but ...
Abstract. We develop a novel, fundamental, and surprisingly simple randomized iterative method for solving consistent linear systems.
The randomized Kaczmarz ($\RK$) algorithm is a simple but powerful approach for solving consistent linear systems $Ax=b$. This paper proposes an accelerated ...
We present an iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov ...
Jun 10, 2015 · Abstract:We develop a novel, fundamental and surprisingly simple randomized iterative method for solving consistent linear systems.
Missing: PRKP: Parallel
Aug 4, 2010 · Abstract. We study randomized variants of two classical algorithms: coordinate descent for systems of linear equations and iterated projections ...