Filters

20211

More filters

20221
Reset filters

Settings

Author: Spokoiny, Vladimir × Subject: Accelerated methods ×

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Stopping rules for accelerated gradient methods with additive noise in gradient
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2021) Vasin, Artem; Gasnikov, Alexander; Spokoiny, Vladimir
    In this article, we investigate an accelerated first-order method, namely, the method of similar triangles, which is optimal in the class of convex (strongly convex) problems with a Lipschitz gradient. The paper considers a model of additive noise in a gradient and a Euclidean prox- structure for not necessarily bounded sets. Convergence estimates are obtained in the case of strong convexity and its absence, and a stopping criterion is proposed for not strongly convex problems.