101 citations · 414 across the 51 of their papers we have counts for
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The global rate of convergence for optimal tensor methods in smooth convex optimization
Alexander Gasnikov, Pavel Dvurechensky, Eduard Gorbunov +3
We consider convex optimization problems with the objective function having Lipshitz-continuous -th order derivative, where . We propose a new tensor method, which clos…
On the upper bound for the mathematical expectation of the norm of a vector uniformly distributed on the sphere and the phenomenon of concentration of uniform measure on the sphere
Eduard Gorbunov, Evgeniya Vorontsova, Alexander Gasnikov
We considered the problem of obtaining upper bounds for the mathematical expectation of the -norm () of the vector which is uniformly distributed…
An Accelerated Directional Derivative Method for Smooth Stochastic Convex Optimization
Pavel Dvurechensky, Eduard Gorbunov, Alexander Gasnikov
We consider smooth stochastic convex optimization problems in the context of algorithms which are based on directional derivatives of the objective function. This context can be co…
Stochastic Spectral and Conjugate Descent Methods
Dmitry Kovalev, Eduard Gorbunov, Elnur Gasanov +1
The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new…
An Accelerated Method for Derivative-Free Smooth Stochastic Convex Optimization
Eduard Gorbunov, Pavel Dvurechensky, Alexander Gasnikov
We consider an unconstrained problem of minimizing a smooth convex function which is only available through noisy observations of its values, the noise consisting of two parts. Sim…