5 citations · 11 across the 5 of their papers we have counts for
6 papers
Optimal spanning tree reconstruction in symbolic regression
Radoslav G. Neychev, Innokentiy A. Shibaev, Vadim V. Strijov
This paper investigates the problem of regression model generation. A model is a superposition of primitive functions. The model structure is described by a weighted colored graph.…
Median Clipping for Zeroth-order Non-Smooth Convex Optimization and Multi-Armed Bandit Problem with Heavy-tailed Symmetric Noise
Nikita Kornilov, Yuriy Dorn, Aleksandr Lobanov +5
In this paper, we consider non-smooth convex optimization with a zeroth-order oracle corrupted by symmetric stochastic noise. Unlike the existing high-probability results requiring…
Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
Nikita Kornilov, Ohad Shamir, Aleksandr Lobanov +5
In this paper, we consider non-smooth stochastic convex optimization with two function evaluations per round under infinite noise variance. In the classical setting when noise has…
High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
Eduard Gorbunov, Marina Danilova, Innokentiy Shibaev +2
Stochastic first-order methods are standard for training large-scale machine learning models. Random behavior may cause a particular run of an algorithm to result in a highly subop…
Recent Theoretical Advances in Non-Convex Optimization
Marina Danilova, Pavel Dvurechensky, Alexander Gasnikov +4
Motivated by recent increased interest in optimization algorithms for non-convex optimization in application to training deep neural networks and other optimization problems in dat…
Zeroth-order methods for noisy Hölder-gradient functions
Innokentiy Shibaev, Pavel Dvurechensky, Alexander Gasnikov
In this paper, we prove new complexity bounds for zeroth-order methods in non-convex optimization with inexact observations of the objective function values. We use the Gaussian sm…