Abstract
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 x k+1 as the projection of x k 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.
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