3 papers
math.OC2024
About some works of Boris Polyak on convergence of gradient methods and their development
Seydamet Ablaev, Aleksandr Beznosikov, Alexander Gasnikov +4
The paper presents a review of the state-of-the-art of subgradient and accelerated methods of convex optimization, including in the presence of disturbances and access to various i…
cs.LG2024
Ruppert-Polyak averaging for Stochastic Order Oracle
V. N. Smirnov, K. M. Kazistova, I. A. Sudakov +3
Black-box optimization, a rapidly growing field, faces challenges due to limited knowledge of the objective function's internal mechanisms. One promising approach to address this i…
math.OC2024
On quasi-convex smooth optimization problems by a comparison oracle
A. V. Gasnikov, M. S. Alkousa, A. V. Lobanov +4
Frequently, when dealing with many machine learning models, optimization problems appear to be challenging due to a limited understanding of the constructions and characterizations…