1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Aligning Distributionally Robust Optimization with Practical Deep Learning Needs
Dmitrii Feoktistov, Igor Ignashin, Andrey Veprikov +4
While traditional Deep Learning (DL) optimization methods treat all training samples equally, Distributionally Robust Optimization (DRO) adaptively assigns importance weights to di…
math.OC2024★ 1 cited
New Aspects of Black Box Conditional Gradient: Variance Reduction and One Point Feedback
Andrey Veprikov, Aleksandr Bogdanov, Vladislav Minashkin +1
This paper deals with the black-box optimization problem. In this setup, we do not have access to the gradient of the objective function, therefore, we need to estimate it somehow.…