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We investigate different randomizations for mirror descent method. We try topropose such a randomization that allows us to use sparsity of the problem asmuch as it possible. In the paper one can also find a generalization ofrandomizaed mirror descent for the convex optimization problems with functionalrestrictions.

Randomization and sparsity in huge-scale optimization on the Mirror Descent example