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We study the problem of minimizing the sum of a smooth convex function and a convex block-separable regularizer and propose a new randomized coordinate descent method, which we call ALPHA.
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Olivier Fercoq and Peter Richtárik · 2013
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On the complexity analysis of randomized block-coordinate descent methods
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On optimal probabilities in stochastic coordinate descent methods
An accelerated proximal coordinate gradient method and its application to regularized empirical risk minimization
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Randomized dual coordinate ascent with arbitrary sampling
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Inexact block coordinate descent method: complexity and preconditioning
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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
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