Nikita Zhivotovskiy

CoRR, April, 2026

Gaussian Width of Convex Sets via Integral Decompositions, Projections, and the Distribution of Intrinsic Volumes.

[BibT_eX]

[DOI]

Reese Pathak

CoRR, March, 2026

Ratio Covers of Convex Sets and Optimal Mixture Density Estimation.

[BibT_eX]

[DOI]

CoRR, February, 2026

Refined Risk Bounds for Unbounded Losses via Transductive Priors.

[BibT_eX]

[DOI]

Jian Qian

Alexander Rakhlin

J. Mach. Learn. Res., 2026

2025

Early science acceleration experiments with GPT-5.

[BibT_eX]

[DOI]

CoRR, November, 2025

Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks.

[BibT_eX]

[DOI]

Omar Montasser

Abhishek Shetty

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

Lower Bounds for Greedy Teaching Set Constructions.

[BibT_eX]

[DOI]

Spencer Compton

Chirag Pabbaraju

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Majority-of-Three: The Simplest Optimal Learner?

[BibT_eX]

[DOI]

Mikael Møller Høgsgaard

CoRR, 2024

Derandomizing Multi-Distribution Learning.

[BibT_eX]

[DOI]

Omar Montasser

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Dimension-free Private Mean Estimation for Anisotropic Distributions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Revisiting Agnostic PAC Learning.

[BibT_eX]

[DOI]

Steve Hanneke

Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

Majority-of-Three: The Simplest Optimal Learner?

[BibT_eX]

[DOI]

Mikael Møller Høandgsgaard

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

High-Probability Risk Bounds via Sequential Predictors.

[BibT_eX]

[DOI]

Dirk van der Hoeven

Nicolò Cesa-Bianchi

CoRR, 2023

Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians.

[BibT_eX]

[DOI]

Arshak Minasyan

CoRR, 2023

Optimal PAC Bounds without Uniform Convergence.

[BibT_eX]

[DOI]

Yeshwanth Cherapanamjeri

Abhishek Shetty

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Exploring Local Norms in Exp-concave Statistical Learning.

[BibT_eX]

[DOI]

Nikita Puchkin

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Local Risk Bounds for Statistical Aggregation.

[BibT_eX]

[DOI]

Jaouad Mourtada

Tomas Vaskevicius

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

The One-Inclusion Graph Algorithm is not Always Optimal.

[BibT_eX]

[DOI]

Yeshwanth Cherapanamjeri

Abhishek Shetty

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Robustifying Markowitz.

[BibT_eX]

[DOI]

CoRR, 2022

A remark on Kashin's discrepancy argument and partial coloring in the Komlós conjecture.

[BibT_eX]

[DOI]

Afonso S. Bandeira

Antoine Maillard

CoRR, 2022

Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails.

[BibT_eX]

[DOI]

Pedro Abdalla

CoRR, 2022

A Regret-Variance Trade-Off in Online Learning.

[BibT_eX]

[DOI]

Dirk van der Hoeven

Nicolò Cesa-Bianchi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Distribution-Free Robust Linear Regression.

[BibT_eX]

[DOI]

Jaouad Mourtada

Tomas Vaskevicius

CoRR, 2021

Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$.

[BibT_eX]

[DOI]

Yegor Klochkov

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exponential savings in agnostic active learning through abstention.

[BibT_eX]

[DOI]

Nikita Puchkin

Proceedings of the Conference on Learning Theory, 2021

2020

When are epsilon-nets small?

[BibT_eX]

[DOI]

Andrey Kupavskii

J. Comput. Syst. Sci., 2020

On Mean Estimation for Heteroscedastic Random Variables.

[BibT_eX]

[DOI]

CoRR, 2020

Suboptimality of Constrained Least Squares and Improvements via Non-Linear Predictors.

[BibT_eX]

[DOI]

Tomas Vaskevicius

CoRR, 2020

Robust k-means Clustering for Distributions with Two Moments.

[BibT_eX]

[DOI]

Yegor Klochkov

Alexey Kroshnin

CoRR, 2020

Fast Rates for Online Prediction with Abstention.

[BibT_eX]

[DOI]

Gergely Neu

Proceedings of the Conference on Learning Theory, 2020

Sharper Bounds for Uniformly Stable Algorithms.

[BibT_eX]

[DOI]

Olivier Bousquet

Yegor Klochkov

Proceedings of the Conference on Learning Theory, 2020

Proper Learning, Helly Number, and an Optimal SVM Bound.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2020

2019

Fast classification rates without standard margin assumptions.

[BibT_eX]

[DOI]

Olivier Bousquet

CoRR, 2019

2017

Optimal learning via local entropies and sample compression.

[BibT_eX]

[DOI]

Proceedings of the 30th Conference on Learning Theory, 2017

2016

Localization of VC Classes: Beyond Local Rademacher Complexities.

[BibT_eX]

[DOI]

Steve Hanneke

Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

2015

Permutational Rademacher Complexity - A New Complexity Measure for Transductive Learning.

[BibT_eX]

[DOI]

Ilya O. Tolstikhin