A class of optimized row projection methods for solving large nonsymmetric linear systems Original Research Article

We present in this paper optimal and accelerated row projection algorithms arising from the use of quadratic programming, that allow us to define the iterate xk+1 as the projection of xk onto a hyperplane which minimizes its distance to the solution x∗. These algorithms also use a novel partition strategy into blocks based on sequential estimations of their condition numbers.