Omar Montasser

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 28

Top Topics

Pac Learnability

Greater Robustness

Digital Image Watermarking

Top Venues

Publications

Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M. Stangl
Agnostic Multi-Robust Learning using ERM. AISTATS (2024)
Han Shao, Avrim Blum, Omar Montasser
Strategic Classification under Unknown Personalized Manipulation. CoRR (2023)
Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin Stangl
Certifiable (Multi)Robustness Against Patch Attacks Using ERM. CoRR (2023)
Omar Montasser
Theoretical Foundations of Adversarially Robust Learning. CoRR (2023)
Han Shao, Avrim Blum, Omar Montasser
Strategic Classification under Unknown Personalized Manipulation. NeurIPS (2023)
Omar Montasser, Steve Hanneke, Nati Srebro
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization. NeurIPS (2022)
Han Shao, Omar Montasser, Avrim Blum
A Theory of PAC Learnability under Transformation Invariances. NeurIPS (2022)
Omar Montasser, Steve Hanneke, Nathan Srebro
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization. CoRR (2022)
Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. CoRR (2022)
Omar Montasser, Steve Hanneke, Nathan Srebro
Transductive Robust Learning Guarantees. AISTATS (2022)
Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. NeurIPS (2022)
Han Shao, Omar Montasser, Avrim Blum
A Theory of PAC Learnability under Transformation Invariances. CoRR (2022)
Omar Montasser, Steve Hanneke, Nathan Srebro
Adversarially Robust Learning with Unknown Perturbation Sets. CoRR (2021)
Omar Montasser, Steve Hanneke, Nathan Srebro
Adversarially Robust Learning with Unknown Perturbation Sets. COLT (2021)
Omar Montasser, Steve Hanneke, Nathan Srebro
Transductive Robust Learning Guarantees. CoRR (2021)
Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
Efficiently Learning Adversarially Robust Halfspaces with Noise. CoRR (2020)
Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples. NeurIPS (2020)
Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
Efficiently Learning Adversarially Robust Halfspaces with Noise. ICML (2020)
Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples. CoRR (2020)
Pritish Kamath, Omar Montasser, Nathan Srebro
Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity. CoRR (2020)
Omar Montasser, Steve Hanneke, Nati Srebro
Reducing Adversarially Robust Learning to Non-Robust PAC Learning. NeurIPS (2020)
Omar Montasser, Steve Hanneke, Nathan Srebro
Reducing Adversarially Robust Learning to Non-Robust PAC Learning. CoRR (2020)
Pritish Kamath, Omar Montasser, Nathan Srebro
Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity. COLT (2020)
Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser
Identifying unpredictable test examples with worst-case guarantees. ITA (2020)
Omar Montasser, Steve Hanneke, Nathan Srebro
VC Classes are Adversarially Robustly Learnable, but Only Improperly. CoRR (2019)
Omar Montasser, Steve Hanneke, Nathan Srebro
VC Classes are Adversarially Robustly Learnable, but Only Improperly. COLT (2019)
Omar Montasser, Daniel Kifer
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. CoRR (2017)
Omar Montasser, Daniel Kifer
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. AAAI (2017)