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We consider smooth stochastic convex optimization problems in the context of algorithms which are based on directional derivatives of the objective function.
Gradient methods for problems with inexact model of the objective
Fedor S. Stonyakin, Darina Dvinskikh, Pavel Dvurechensky, Alexey Kroshnin, Olesya Kuznetsova, Artem Agafonov, Alexander Gasnikov, Alexander Tyurin, César A. Uribe, Dmitry Pasechnyuk, and Sergei Artamonov · 1902
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On primal and dual approaches for distributed stochastic convex optimization over networks
Darina Dvinskikh, Eduard Gorbunov, Alexander Gasnikov, Pavel Dvurechensky, and Cesar A. Uribe · 1903
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Aleksandr Beznosikov, Eduard Gorbunov, and Alexander Gasnikov · 1911
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