12 citations · 22 across the 4 of their papers we have counts for
4 papers · 1 filter
Method with Batching for Stochastic Finite-Sum Variational Inequalities in Non-Euclidean Setting
Alexander Pichugin, Maksim Pechin, Aleksandr Beznosikov +2
Variational inequalities are a universal optimization paradigm that incorporate classical minimization and saddle point problems. Nowadays more and more tasks require to consider s…
The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems
Alexander Gasnikov, Anton Novitskii, Vasilii Novitskii +6
Gradient-free/zeroth-order methods for black-box convex optimization have been extensively studied in the last decade with the main focus on oracle calls complexity. In this paper,…
One-Point Gradient-Free Methods for Smooth and Non-Smooth Saddle-Point Problems
Aleksandr Beznosikov, Vasilii Novitskii, Alexander Gasnikov
In this paper, we analyze gradient-free methods with one-point feedback for stochastic saddle point problems . For non-smooth and smooth cases, we present…
Improved Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandit
Vasilii Novitskii, Alexander Gasnikov
We consider -smooth (satisfies the generalized Holder condition with parameter ) stochastic convex optimization problem with zero-order one-point oracle. The best known re…