Idan Attias

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 23

Top Topics

Generalization Bounds

Online Learning

Pac Learnability

Convex Optimization

Top Venues

Publications

Ziyi Liu, Idan Attias, Daniel M. Roy
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals. CoRR (2024)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT (2024)
Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization. CoRR (2024)
Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. ITCS (2023)
Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson
Online Learning and Solving Infinite Games with an ERM Oracle. CoRR (2023)
Eitan-Hai Mashiah, Idan Attias, Yishay Mansour
Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers. AAAI (2023)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS (2023)
Idan Attias, Steve Hanneke
Adversarially Robust PAC Learnability of Real-Valued Functions. ICML (2023)
Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell K. Fishelson
Online Learning and Solving Infinite Games with an ERM Oracle. COLT (2023)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR (2023)
Eitan-Hai Mashiah, Idan Attias, Yishay Mansour
Stochastic Strategic Patient Buyers: Revenue maximization using posted prices. CoRR (2022)
Idan Attias, Aryeh Kontorovich, Yishay Mansour
Improved Generalization Bounds for Adversarially Robust Learning. J. Mach. Learn. Res. 23 (2022)
Idan Attias, Steve Hanneke
Adversarially Robust Learning of Real-Valued Functions. CoRR (2022)
Idan Attias, Steve Hanneke, Yishay Mansour
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability. CoRR (2022)
Matan Levi, Idan Attias, Aryeh Kontorovich
Domain Invariant Adversarial Learning. Trans. Mach. Learn. Res. 2022 (2022)
Idan Attias, Steve Hanneke, Yishay Mansour
A Characterization of Semi-Supervised Adversarially Robust PAC Learnability. NeurIPS (2022)
Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. CoRR (2021)
Matan Levi, Idan Attias, Aryeh Kontorovich
Domain Invariant Adversarial Learning. CoRR (2021)
Aryeh Kontorovich, Idan Attias
Fat-shattering dimension of k-fold maxima. CoRR (2021)
Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni
Prediction with Corrupted Expert Advice. NeurIPS (2020)
Idan Amir, Idan Attias, Tomer Koren, Roi Livni, Yishay Mansour
Prediction with Corrupted Expert Advice. CoRR (2020)
Idan Attias, Aryeh Kontorovich, Yishay Mansour
Improved Generalization Bounds for Robust Learning. ALT (2019)
Idan Attias, Aryeh Kontorovich, Yishay Mansour
Improved generalization bounds for robust learning. CoRR (2018)