Nikita Zhivotovskiy

55 papers A* 17B 2Journal 36

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Gaussian Width of Convex Sets via Integral Decompositions, Projections, and the Distribution of Intrinsic Volumes. CoRR Reese Pathak, Nikita Zhivotovskiy
2026	J	`jnl`	Ratio Covers of Convex Sets and Optimal Mixture Density Estimation. CoRR Spencer Compton, Gábor Lugosi, Jaouad Mourtada, Jian Qian, Nikita Zhivotovskiy
2026	J	`jnl`	Refined Risk Bounds for Unbounded Losses via Transductive Priors. J. Mach. Learn. Res. Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy
2025	A*	`conf`	Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks. COLT Omar Montasser, Abhishek Shetty, Nikita Zhivotovskiy
2025	J	`jnl`	Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks. CoRR Omar Montasser, Abhishek Shetty, Nikita Zhivotovskiy
2025	J	`jnl`	Early science acceleration experiments with GPT-5. CoRR Sébastien Bubeck, Christian Coester, Ronen Eldan, Timothy Gowers, Yin Tat Lee, Alexandru Lupsasca, Mehtaab Sawhney, Robert Scherrer, Mark Sellke, Brian K. Spears, Derya Unutmaz, Kevin Weil, Steven Yin, Nikita Zhivotovskiy
2025	A*	`conf`	Lower Bounds for Greedy Teaching Set Constructions. COLT Spencer Compton, Chirag Pabbaraju, Nikita Zhivotovskiy
2025	J	`jnl`	Lower Bounds for Greedy Teaching Set Constructions. CoRR Spencer Compton, Chirag Pabbaraju, Nikita Zhivotovskiy
2024	A*	`conf`	Derandomizing Multi-Distribution Learning. NeurIPS Kasper Green Larsen, Omar Montasser, Nikita Zhivotovskiy
2024	J	`jnl`	Derandomizing Multi-Distribution Learning. CoRR Kasper Green Larsen, Omar Montasser, Nikita Zhivotovskiy
2024	A*	`conf`	Dimension-free Private Mean Estimation for Anisotropic Distributions. NeurIPS Yuval Dagan, Michael I. Jordan, Xuelin Yang, Lydia Zakynthinou, Nikita Zhivotovskiy
2024	J	`jnl`	Dimension-free Private Mean Estimation for Anisotropic Distributions. CoRR Yuval Dagan, Michael I. Jordan, Xuelin Yang, Lydia Zakynthinou, Nikita Zhivotovskiy
2024	A*	`conf`	Majority-of-Three: The Simplest Optimal Learner? COLT Ishaq Aden-Ali, Mikael Møller Høandgsgaard, Kasper Green Larsen, Nikita Zhivotovskiy
2024	J	`jnl`	Majority-of-Three: The Simplest Optimal Learner? CoRR Ishaq Aden-Ali, Mikael Møller Høgsgaard, Kasper Green Larsen, Nikita Zhivotovskiy
2024	J	`jnl`	Refined Risk Bounds for Unbounded Losses via Transductive Priors. CoRR Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy
2024	A*	`conf`	Revisiting Agnostic PAC Learning. FOCS Steve Hanneke, Kasper Green Larsen, Nikita Zhivotovskiy
2024	J	`jnl`	Revisiting Agnostic PAC Learning. CoRR Steve Hanneke, Kasper Green Larsen, Nikita Zhivotovskiy
2023	A*	`conf`	Exploring Local Norms in Exp-concave Statistical Learning. COLT Nikita Puchkin, Nikita Zhivotovskiy
2023	J	`jnl`	Exploring Local Norms in Exp-concave Statistical Learning. CoRR Nikita Puchkin, Nikita Zhivotovskiy
2023	J	`jnl`	High-Probability Risk Bounds via Sequential Predictors. CoRR Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
2023	A*	`conf`	Local Risk Bounds for Statistical Aggregation. COLT Jaouad Mourtada, Tomas Vaskevicius, Nikita Zhivotovskiy
2023	J	`jnl`	Local Risk Bounds for Statistical Aggregation. CoRR Jaouad Mourtada, Tomas Vaskevicius, Nikita Zhivotovskiy
2023	J	`jnl`	Optimal PAC Bounds Without Uniform Convergence. CoRR Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2023	A*	`conf`	Optimal PAC Bounds without Uniform Convergence. FOCS Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2023	J	`jnl`	Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians. CoRR Arshak Minasyan, Nikita Zhivotovskiy
2023	A*	`conf`	The One-Inclusion Graph Algorithm is not Always Optimal. COLT Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2022	A*	`conf`	A Regret-Variance Trade-Off in Online Learning. NeurIPS Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
2022	J	`jnl`	A Regret-Variance Trade-Off in Online Learning. CoRR Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
2022	J	`jnl`	A remark on Kashin's discrepancy argument and partial coloring in the Komlós conjecture. CoRR Afonso S. Bandeira, Antoine Maillard, Nikita Zhivotovskiy
2022	J	`jnl`	Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails. CoRR Pedro Abdalla, Nikita Zhivotovskiy
2022	J	`jnl`	Exponential Savings in Agnostic Active Learning Through Abstention. IEEE Trans. Inf. Theory Nikita Puchkin, Nikita Zhivotovskiy
2022	J	`jnl`	Robustifying Markowitz. CoRR Wolfgang Karl Härdle, Yegor Klochkov, Alla Petukhina, Nikita Zhivotovskiy
2022	J	`jnl`	The One-Inclusion Graph Algorithm is not Always Optimal. CoRR Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2021	J	`jnl`	Distribution-Free Robust Linear Regression. CoRR Jaouad Mourtada, Tomas Vaskevicius, Nikita Zhivotovskiy
2021	J	`jnl`	Exponential Savings in Agnostic Active Learning through Abstention. CoRR Nikita Puchkin, Nikita Zhivotovskiy
2021	A*	`conf`	Exponential savings in agnostic active learning through abstention. COLT Nikita Puchkin, Nikita Zhivotovskiy
2021	A*	`conf`	Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$. NeurIPS Yegor Klochkov, Nikita Zhivotovskiy
2021	J	`jnl`	Stability and Deviation Optimal Risk Bounds with Convergence Rate O(1/n). CoRR Yegor Klochkov, Nikita Zhivotovskiy
2020	A*	`conf`	Fast Rates for Online Prediction with Abstention. COLT Gergely Neu, Nikita Zhivotovskiy
2020	J	`jnl`	Fast Rates for Online Prediction with Abstention. CoRR Gergely Neu, Nikita Zhivotovskiy
2020	J	`jnl`	On Mean Estimation for Heteroscedastic Random Variables. CoRR Luc Devroye, Silvio Lattanzi, Gábor Lugosi, Nikita Zhivotovskiy
2020	A*	`conf`	Proper Learning, Helly Number, and an Optimal SVM Bound. COLT Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy
2020	J	`jnl`	Proper Learning, Helly Number, and an Optimal SVM Bound. CoRR Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy
2020	J	`jnl`	Robust k-means Clustering for Distributions with Two Moments. CoRR Yegor Klochkov, Alexey Kroshnin, Nikita Zhivotovskiy
2020	A*	`conf`	Sharper Bounds for Uniformly Stable Algorithms. COLT Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy
2020	J	`jnl`	Suboptimality of Constrained Least Squares and Improvements via Non-Linear Predictors. CoRR Tomas Vaskevicius, Nikita Zhivotovskiy
2020	J	`jnl`	When are epsilon-nets small? J. Comput. Syst. Sci. Andrey Kupavskii, Nikita Zhivotovskiy
2019	J	`jnl`	Fast classification rates without standard margin assumptions. CoRR Olivier Bousquet, Nikita Zhivotovskiy
2019	J	`jnl`	Sharper bounds for uniformly stable algorithms. CoRR Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy
2018	J	`jnl`	Localization of VC classes: Beyond local Rademacher complexities. Theor. Comput. Sci. Nikita Zhivotovskiy, Steve Hanneke
2017	A*	`conf`	Optimal learning via local entropies and sample compression. COLT Nikita Zhivotovskiy
2017	J	`jnl`	When are epsilon-nets small? CoRR Andrey Kupavskii, Nikita Zhivotovskiy
2016	B	`conf`	Localization of VC Classes: Beyond Local Rademacher Complexities. ALT Nikita Zhivotovskiy, Steve Hanneke
2015	B	`conf`	Permutational Rademacher Complexity - A New Complexity Measure for Transductive Learning. ALT Ilya O. Tolstikhin, Nikita Zhivotovskiy, Gilles Blanchard
2015	J	`jnl`	Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning. CoRR Ilya O. Tolstikhin, Nikita Zhivotovskiy, Gilles Blanchard