6 citations · 11 across the 7 of their papers we have counts for
8 papers
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits
Yuriy Dorn, Nikita Kornilov, Nikolay Kutuzov +3
The Implicitly Normalized Forecaster (INF) algorithm is considered to be an optimal solution for adversarial multi-armed bandit (MAB) problems. However, most of the existing comple…
Algorithms of Robust Stochastic Optimization Based on Mirror Descent Method
Anatoli Juditsky, Alexander Nazin, Arkadi Nemirovsky +1
We propose an approach to construction of robust non-Euclidean iterative algorithms for convex composite stochastic optimization based on truncation of stochastic gradients. For su…
Two-Armed Bandit Problem, Data Processing, and Parallel Version of the Mirror Descent Algorithm
Alexander Kolnogorov, Alexander Nazin, Dmitry Shiyan
We consider the minimax setup for the two-armed bandit problem as applied to data processing if there are two alternative processing methods available with different a priori unkno…
Algorithms of Inertial Mirror Descent in Convex Problems of Stochastic Optimization
Alexander Nazin
The goal is to modify the known method of mirror descent (MD), proposed by A.S. Nemirovsky and D.B. Yudin in 1979. The paper shows the idea of a new, so-called inertial MD method w…
L1-optimal linear programming estimatorfor periodic frontier functions with Holder continuous derivative
Alexander Nazin, Stephane Girard
We propose a new estimator based on a linear programming method for smooth frontiers of sample points. The derivative of the frontier function is supposed to be Holder continuous.T…
Linear programming problems for frontier estimation
Guillaume Bouchard, Stéphane Girard, Anatoli Iouditski +1
We propose new estimates for the frontier of a set of points. They are defined as kernel estimates covering all the points and whose associated support is of smallest surface. The…