Moran, Shay

68 publications

COLT 2025 A Fine-Grained Characterization of PAC Learnability Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

NeurIPS 2025 Agnostic Learning Under Targeted Poisoning: Optimal Rates and the Role of Randomness Bogdan Chornomaz, Yonatan Koren, Shay Moran, Tom Waknine

COLT 2025 Data Selection for ERMs Steve Hanneke, Shay Moran, Alexander Shlimovich, Amir Yehudayoff

NeurIPS 2025 Marginal-Nonuniform PAC Learnability Steve Hanneke, Shay Moran, Maximilian Thiessen

COLT 2025 Of Dice and Games: A Theory of Generalized Boosting Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

COLT 2025 Open Problem: Data Selection for Regression Tasks Steve Hanneke, Shay Moran, Alexander Shlimovich, Amir Yehudayoff

NeurIPS 2025 Optimal Mistake Bounds for Transductive Online Learning Zachary Chase, Steve Hanneke, Shay Moran, Jonathan Shafer

COLT 2025 Private List Learnability vs. Online List Learnability Steve Hanneke, Shay Moran, Hilla Schefler, Iska Tsubari

NeurIPS 2025 Probably Approximately Precision and Recall Learning Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

NeurIPS 2025 Reconstruction and Secrecy Under Approximate Distance Queries Shay Moran, Elizaveta Nesterova

COLT 2025 Spherical Dimension Bogdan Chornomaz, Shay Moran, Tom Waknine

ICML 2025 The Role of Randomness in Stability Max Hopkins, Shay Moran

COLT 2024 A Theory of Interpretable Approximations Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

NeurIPSW 2024 A Theory of Interpretable Approximations Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen

COLT 2024 A Unified Characterization of Private Learnability via Graph Theory Noga Alon, Shay Moran, Hilla Schefler, Amir Yehudayoff

NeurIPS 2024 Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran

NeurIPS 2024 Credit Attribution and Stable Compression Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju

COLT 2024 Dual VC Dimension Obstructs Sample Compression by Embeddings Zachary Chase, Bogdan Chornomaz, Steve Hanneke, Shay Moran, Amir Yehudayoff

NeurIPS 2024 Fast Rates for Bandit PAC Multiclass Classification Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran

NeurIPS 2024 Improved Sample Complexity for Multiclass PAC Learning Steve Hanneke, Shay Moran, Qian Zhang

COLT 2024 Learnability Gaps of Strategic Classification Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

NeurIPS 2024 Learning-Augmented Algorithms with Explicit Predictors Marek Eliáš, Haim Kaplan, Yishay Mansour, Shay Moran

COLT 2024 List Sample Compression and Uniform Convergence Steve Hanneke, Shay Moran, Waknine Tom

COLT 2024 Open Problem: Direct Sums in Learning Theory Steve Hanneke, Shay Moran, Waknine Tom

COLT 2024 The Real Price of Bandit Information in Multiclass Classification Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran

NeurIPS 2024 Universal Rates for Active Learning Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas

NeurIPS 2023 A Trichotomy for Transductive Online Learning Steve Hanneke, Shay Moran, Jonathan Shafer

NeurIPS 2023 Adversarial Resilience in Sequential Prediction via Abstention Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty

NeurIPS 2023 Black-Box Differential Privacy for Interactive ML Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer

NeurIPSW 2023 Can Copyright Be Reduced to Privacy Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran

COLT 2023 Fine-Grained Distribution-Dependent Learning Curves Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya Tolstikhin

COLT 2023 Improper Multiclass Boosting Nataly Brukhim, Steve Hanneke, Shay Moran

COLT 2023 List Online Classification Shay Moran, Ohad Sharon, Iska Tsubari, Sivan Yosebashvili

NeurIPS 2023 Multiclass Boosting: Simple and Intuitive Weak Learning Criteria Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran

COLT 2023 Multiclass Online Learning and Uniform Convergence Steve Hanneke, Shay Moran, Vinod Raman, Unique Subedi, Ambuj Tewari

COLT 2023 Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension Yuval Filmus, Steve Hanneke, Idan Mehalel, Shay Moran

ICML 2023 Statistical Indistinguishability of Learning Algorithms Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas

NeurIPS 2023 The Bayesian Stability Zoo Shay Moran, Hilla Schefler, Jonathan Shafer

COLT 2023 Universal Rates for Multiclass Learning Steve Hanneke, Shay Moran, Qian Zhang

ICML 2022 A Resilient Distributed Boosting Algorithm Yuval Filmus, Idan Mehalel, Shay Moran

UAI 2022 Active Learning with Label Comparisons Gal Yona, Shay Moran, Gal Elidan, Amir Globerson

NeurIPS 2022 Integral Probability Metrics PAC-Bayes Bounds Ron Amit, Baruch Epstein, Shay Moran, Ron Meir

COLT 2022 Monotone Learning Olivier J Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer

NeurIPS 2022 On Optimal Learning Under Targeted Data Poisoning Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran

NeurIPS 2022 Universal Rates for Interactive Learning Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas

NeurIPS 2021 Multiclass Boosting and the Cost of Weak Learning Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire

COLT 2021 Near Optimal Distributed Learning of Halfspaces with Two Parties Mark Braverman, Gillat Kol, Shay Moran, Raghuvansh R. Saxena

COLT 2021 Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games Steve Hanneke, Roi Livni, Shay Moran

NeurIPS 2021 Towards a Unified Information-Theoretic Framework for Generalization Mahdi Haghifam, Gintare Karolina Dziugaite, Shay Moran, Dan Roy

NeurIPS 2020 A Limitation of the PAC-Bayes Framework Roi Livni, Shay Moran

COLT 2020 Closure Properties for Private Classification and Online Prediction Noga Alon, Amos Beimel, Shay Moran, Uri Stemmer

NeurIPS 2020 Learning from Mixtures of Private and Public Populations Raef Bassily, Shay Moran, Anupama Nandi

NeurIPS 2020 Online Agnostic Boosting via Regret Minimization Nataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran

ICML 2020 Private Query Release Assisted by Public Data Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan Ullman, Steven Wu

COLT 2020 Proper Learning, Helly Number, and an Optimal SVM Bound Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy

NeurIPS 2020 Synthetic Data Generators -- Sequential and Private Olivier Bousquet, Roi Livni, Shay Moran

NeurIPS 2019 An Adaptive Nearest Neighbor Rule for Classification Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran

NeurIPS 2019 Learning to Screen Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran

NeurIPS 2019 Limits of Private Learning with Access to Public Data Noga Alon, Raef Bassily, Shay Moran

COLT 2019 On Communication Complexity of Classification Problems Daniel Kane, Roi Livni, Shay Moran, Amir Yehudayoff

COLT 2019 Private Center Points and Learning of Halfspaces Amos Beimel, Shay Moran, Kobbi Nissim, Uri Stemmer

NeurIPS 2019 Private Learning Implies Online Learning: An Efficient Reduction Alon Gonen, Elad Hazan, Shay Moran

COLT 2019 The Optimal Approximation Factor in Density Estimation Olivier Bousquet, Daniel Kane, Shay Moran

ALT 2018 Learners That Use Little Information Raef Bassily, Shay Moran, Ido Nachum, Jonathan Shafer, Amir Yehudayoff

NeurIPS 2017 Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues Noga Alon, Moshe Babaioff, Yannai A. Gonczarowski, Yishay Mansour, Shay Moran, Amir Yehudayoff

ALT 2016 Labeled Compression Schemes for Extremal Classes Shay Moran, Manfred K. Warmuth

COLT 2016 Sign Rank Versus VC Dimension Noga Alon, Shay Moran, Amir Yehudayoff

NeurIPS 2016 Supervised Learning Through the Lens of Compression Ofir David, Shay Moran, Amir Yehudayoff