Montasser, Omar

20 publications

COLT 2025 Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks Omar Montasser, Abhishek Shetty, Nikita Zhivotovskiy

NeurIPS 2025 CoT Information: Improved Sample Complexity Under Chain-of-Thought Supervision Awni Altabaa, Omar Montasser, John Lafferty

ICLRW 2025 DDPM Score Matching Is Asymptotically Efficient Sinho Chewi, Alkis Kalavasis, Anay Mehrotra, Omar Montasser

NeurIPS 2025 Sample-Adaptivity Tradeoff in On-Demand Sampling Nika Haghtalab, Omar Montasser, Mingda Qiao

AISTATS 2024 Agnostic Multi-Robust Learning Using ERM Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M Stangl

NeurIPS 2024 Derandomizing Multi-Distribution Learning Kasper Green Larsen, Omar Montasser, Nikita Zhivotovskiy

NeurIPS 2024 Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization Omar Montasser, Han Shao, Emmanuel Abbe

NeurIPS 2023 Strategic Classification Under Unknown Personalized Manipulation Han Shao, Avrim Blum, Omar Montasser

AISTATS 2022 Transductive Robust Learning Guarantees Omar Montasser, Steve Hanneke, Nathan Srebro

NeurIPS 2022 A Theory of PAC Learnability Under Transformation Invariances Han Shao, Omar Montasser, Avrim Blum

NeurIPS 2022 Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization Omar Montasser, Steve Hanneke, Nati Srebro

NeurIPS 2022 Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang

NeurIPSW 2022 Certifiable Robustness Against Patch Attacks Using an ERM Oracle Kevin Stangl, Avrim Blum, Omar Montasser, Saba Ahmadi

COLT 2021 Adversarially Robust Learning with Unknown Perturbation Sets Omar Montasser, Steve Hanneke, Nathan Srebro

COLT 2020 Approximate Is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity Pritish Kamath, Omar Montasser, Nathan Srebro

NeurIPS 2020 Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser

ICML 2020 Efficiently Learning Adversarially Robust Halfspaces with Noise Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro

NeurIPS 2020 Reducing Adversarially Robust Learning to Non-Robust PAC Learning Omar Montasser, Steve Hanneke, Nati Srebro

COLT 2019 VC Classes Are Adversarially Robustly Learnable, but Only Improperly Omar Montasser, Steve Hanneke, Nathan Srebro

AAAI 2017 Predicting Demographics of High-Resolution Geographies with Geotagged Tweets Omar Montasser, Daniel Kifer