 Differential privacy from axiomsInformation Technology Convergence and Services (ITCS), 2025 |
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 Private List Learnability vs. Online List LearnabilityAnnual Conference Computational Learning Theory (COLT), 2025 |
 Replicable Uniformity TestingNeural Information Processing Systems (NeurIPS), 2024 |
 Calibrating Noise for Group Privacy in Subsampled MechanismsProceedings of the VLDB Endowment (PVLDB), 2024 |
 Local Borsuk-Ulam, Stability, and ReplicabilitySymposium on the Theory of Computing (STOC), 2023 |
 The Bayesian Stability ZooNeural Information Processing Systems (NeurIPS), 2023 |
 Optimal Guarantees for Algorithmic Reproducibility and Gradient
Complexity in Convex OptimizationNeural Information Processing Systems (NeurIPS), 2023 |
 User-Level Differential Privacy With Few Examples Per UserNeural Information Processing Systems (NeurIPS), 2023 |
 Simple online learning with consistent oracleAnnual Conference Computational Learning Theory (COLT), 2023 |
 Optimal Learners for Realizable Regression: PAC Learning and Online
LearningNeural Information Processing Systems (NeurIPS), 2023 |
 Replicability in Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023 |
 Replicable Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023 |
 Statistical Indistinguishability of Learning AlgorithmsInternational Conference on Machine Learning (ICML), 2023 |
 A Unified Characterization of Private Learnability via Graph TheoryAnnual Conference Computational Learning Theory (COLT), 2023 |
 Replicable ClusteringNeural Information Processing Systems (NeurIPS), 2023 |
