Shay Moran

Learning Conditional Averages COLT 2026 Learning from Equivalence Queries, Revisited COLT 2026 Margin in Abstract Spaces COLT 2026 Optimal Reconstruction from Linear Queries COLT 2026 The Sample Complexity of Multiclass and Sparse Contextual Bandits COLT 2026 Uniform Laws of Large Numbers in Product Spaces COLT 2026 A Fine-grained Characterization of PAC Learnability COLT 2025 Data Selection for ERMs COLT 2025 Of Dice and Games: A Theory of Generalized Boosting COLT 2025 Open Problem: Data Selection for Regression Tasks COLT 2025 Private List Learnability vs. Online List Learnability COLT 2025 Spherical Dimension COLT 2025 The Role of Randomness in Stability ICML 2025 A Theory of Interpretable Approximations COLT 2024 A Unified Characterization of Private Learnability via Graph Theory COLT 2024 Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs NeurIPS 2024 Credit Attribution and Stable Compression NeurIPS 2024 Dual VC Dimension Obstructs Sample Compression by Embeddings COLT 2024 Fast Rates for Bandit PAC Multiclass Classification NeurIPS 2024 Improved Sample Complexity for Multiclass PAC Learning NeurIPS 2024 Learnability Gaps of Strategic Classification COLT 2024 Learning-Augmented Algorithms with Explicit Predictors NeurIPS 2024 List Sample Compression and Uniform Convergence COLT 2024 Open problem: Direct Sums in Learning Theory COLT 2024 The Real Price of Bandit Information in Multiclass Classification COLT 2024 Universal Rates for Active Learning NeurIPS 2024 Adversarial Resilience in Sequential Prediction via Abstention NeurIPS 2023 A Trichotomy for Transductive Online Learning NeurIPS 2023 Black-Box Differential Privacy for Interactive ML NeurIPS 2023 Fine-Grained Distribution-Dependent Learning Curves COLT 2023 Improper Multiclass Boosting COLT 2023 List Online Classification COLT 2023 Multiclass Boosting: Simple and Intuitive Weak Learning Criteria NeurIPS 2023 Multiclass Online Learning and Uniform Convergence COLT 2023 Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension COLT 2023 Statistical Indistinguishability of Learning Algorithms ICML 2023 The Bayesian Stability Zoo NeurIPS 2023 Universal Rates for Multiclass Learning COLT 2023 Active learning with label comparisons UAI 2022 A Resilient Distributed Boosting Algorithm ICML 2022 Integral Probability Metrics PAC-Bayes Bounds NeurIPS 2022 Monotone Learning COLT 2022 On Optimal Learning Under Targeted Data Poisoning NeurIPS 2022 Universal Rates for Interactive Learning NeurIPS 2022 Multiclass Boosting and the Cost of Weak Learning NeurIPS 2021 Near Optimal Distributed Learning of Halfspaces with Two Parties COLT 2021 Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021 Towards a Unified Information-Theoretic Framework for Generalization NeurIPS 2021 A Limitation of the PAC-Bayes Framework NeurIPS 2020 Closure Properties for Private Classification and Online Prediction COLT 2020 Learning from Mixtures of Private and Public Populations NeurIPS 2020 Online Agnostic Boosting via Regret Minimization NeurIPS 2020 Private Query Release Assisted by Public Data ICML 2020 Proper Learning, Helly Number, and an Optimal SVM Bound COLT 2020 Synthetic Data Generators -- Sequential and Private NeurIPS 2020 An adaptive nearest neighbor rule for classification NeurIPS 2019 Learning to Screen NeurIPS 2019 Limits of Private Learning with Access to Public Data NeurIPS 2019 On Communication Complexity of Classification Problems COLT 2019 Private Center Points and Learning of Halfspaces COLT 2019 Private Learning Implies Online Learning: An Efficient Reduction NeurIPS 2019 The Optimal Approximation Factor in Density Estimation COLT 2019 Learners that Use Little Information ALT 2018 Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues NeurIPS 2017 Sign rank versus VC dimension COLT 2016 Supervised learning through the lens of compression NeurIPS 2016