activity
20162026
most citedProper Learning, Helly Number, and an Optimal SVM Bound

7 citations · 14 across the 12 of their papers we have counts for

collaborators

30 papers

math.PR2026

A remark on the majorizing measures theorem for general processes

Reese Pathak, Nikita Zhivotovskiy

We show that the lower bound in the majorizing measures theorem holds for a large class of random vectors. Specifically, suppose is a centered random vector in $\mathbf{…

cs.LG2023

High-Probability Risk Bounds via Sequential Predictors

Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi

Online learning methods yield sequential regret bounds under minimal assumptions and provide in-expectation risk bounds for statistical learning. However, despite the apparent adva…

math.ST2023

Local Risk Bounds for Statistical Aggregation

Jaouad Mourtada, Tomas Vaškevičius, Nikita Zhivotovskiy

In the problem of aggregation, the aim is to combine a given class of base predictors to achieve predictions nearly as accurate as the best one. In this flexible framework, no assu…

cs.LG2023

Optimal PAC Bounds Without Uniform Convergence

Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty +1

In statistical learning theory, determining the sample complexity of realizable binary classification for VC classes was a long-standing open problem. The results of Simon and Hann…

cs.LG2023

Exploring Local Norms in Exp-concave Statistical Learning

Nikita Puchkin, Nikita Zhivotovskiy

We consider the problem of stochastic convex optimization with exp-concave losses using Empirical Risk Minimization in a convex class. Answering a question raised in several prior…

math.ST2023★ 3 cited

Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians

Arshak Minasyan, Nikita Zhivotovskiy

Assume that is an -contaminated sample of independent Gaussian vectors in with mean and covariance . In the strong $\v…