Omar Montasser

38 papers A* 14A 2Misc 1Journal 21

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	(Im)possibility of Automated Hallucination Detection in Large Language Models. CoRR Amin Karbasi, Omar Montasser, John Sous, Grigoris Velegkas
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`	CoT Information: Improved Sample Complexity under Chain-of-Thought Supervision. CoRR Awni Altabaa, Omar Montasser, John Lafferty
2025	J	`jnl`	DDPM Score Matching and Distribution Learning. CoRR Sinho Chewi, Alkis Kalavasis, Anay Mehrotra, Omar Montasser
2025	J	`jnl`	Sample-Adaptivity Tradeoff in On-Demand Sampling. CoRR Nika Haghtalab, Omar Montasser, Mingda Qiao
2024	A	`conf`	Agnostic Multi-Robust Learning using ERM. AISTATS Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M. Stangl
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`	Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization. NeurIPS Omar Montasser, Han Shao, Emmanuel Abbe
2024	J	`jnl`	Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization. CoRR Omar Montasser, Han Shao, Emmanuel Abbe
2023	J	`jnl`	Certifiable (Multi)Robustness Against Patch Attacks Using ERM. CoRR Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin Stangl
2023	A*	`conf`	Strategic Classification under Unknown Personalized Manipulation. NeurIPS Han Shao, Avrim Blum, Omar Montasser
2023	J	`jnl`	Strategic Classification under Unknown Personalized Manipulation. CoRR Han Shao, Avrim Blum, Omar Montasser
2023	J	`jnl`	Theoretical Foundations of Adversarially Robust Learning. CoRR Omar Montasser
2022	A*	`conf`	A Theory of PAC Learnability under Transformation Invariances. NeurIPS Han Shao, Omar Montasser, Avrim Blum
2022	J	`jnl`	A Theory of PAC Learnability under Transformation Invariances. CoRR Han Shao, Omar Montasser, Avrim Blum
2022	A*	`conf`	Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization. NeurIPS Omar Montasser, Steve Hanneke, Nati Srebro
2022	J	`jnl`	Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization. CoRR Omar Montasser, Steve Hanneke, Nathan Srebro
2022	A*	`conf`	Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. NeurIPS Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
2022	J	`jnl`	Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. CoRR Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
2022	A	`conf`	Transductive Robust Learning Guarantees. AISTATS Omar Montasser, Steve Hanneke, Nathan Srebro
2021	A*	`conf`	Adversarially Robust Learning with Unknown Perturbation Sets. COLT Omar Montasser, Steve Hanneke, Nathan Srebro
2021	J	`jnl`	Adversarially Robust Learning with Unknown Perturbation Sets. CoRR Omar Montasser, Steve Hanneke, Nathan Srebro
2021	J	`jnl`	Transductive Robust Learning Guarantees. CoRR Omar Montasser, Steve Hanneke, Nathan Srebro
2020	A*	`conf`	Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity. COLT Pritish Kamath, Omar Montasser, Nathan Srebro
2020	J	`jnl`	Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity. CoRR Pritish Kamath, Omar Montasser, Nathan Srebro
2020	A*	`conf`	Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples. NeurIPS Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser
2020	J	`jnl`	Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples. CoRR Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser
2020	A*	`conf`	Efficiently Learning Adversarially Robust Halfspaces with Noise. ICML Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
2020	J	`jnl`	Efficiently Learning Adversarially Robust Halfspaces with Noise. CoRR Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
2020	Misc	`conf`	Identifying unpredictable test examples with worst-case guarantees. ITA Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser
2020	A*	`conf`	Reducing Adversarially Robust Learning to Non-Robust PAC Learning. NeurIPS Omar Montasser, Steve Hanneke, Nati Srebro
2020	J	`jnl`	Reducing Adversarially Robust Learning to Non-Robust PAC Learning. CoRR Omar Montasser, Steve Hanneke, Nathan Srebro
2019	A*	`conf`	VC Classes are Adversarially Robustly Learnable, but Only Improperly. COLT Omar Montasser, Steve Hanneke, Nathan Srebro
2019	J	`jnl`	VC Classes are Adversarially Robustly Learnable, but Only Improperly. CoRR Omar Montasser, Steve Hanneke, Nathan Srebro
2017	A*	`conf`	Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. AAAI Omar Montasser, Daniel Kifer
2017	J	`jnl`	Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. CoRR Omar Montasser, Daniel Kifer