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Idan Attias
Idan Attias
PhD candidate, Ben Gurion University
Verified email at post.bgu.ac.il - Homepage
Title
Cited by
Cited by
Year
Improved generalization bounds for adversarially robust learning
I Attias, A Kontorovich, Y Mansour
Journal of Machine Learning Research 23 (175), 1-31, 2022
103*2022
Prediction with Corrupted Expert Advice
I Amir, I Attias, T Koren, R Livni, Y Mansour
Advances in Neural Information Processing Systems 33, 2020
352020
A framework for adversarial streaming via differential privacy and difference estimators
I Attias, E Cohen, M Shechner, U Stemmer
Innovations in Theoretical Computer Science Conference (2023), 2021
282021
A characterization of semi-supervised adversarially robust pac learnability
I Attias, S Hanneke, Y Mansour
Advances in Neural Information Processing Systems 35, 23646-23659, 2022
132022
Fat-Shattering Dimension of k-fold Aggregations
I Attias, A Kontorovich
Journal of Machine Learning Research 25 (144), 1-29, 2024
12*2024
Domain invariant adversarial learning
M Levi, I Attias, A Kontorovich
Transactions on Machine Learning Research (2022), 2021
122021
Optimal learners for realizable regression: Pac learning and online learning
I Attias, S Hanneke, A Kalavasis, A Karbasi, G Velegkas
Advances in Neural Information Processing Systems 36, 2023
112023
Adversarially Robust PAC Learnability of Real-Valued Functions
I Attias, S Hanneke
International Conference on Machine Learning, 1172-1199, 2023
112023
Online learning and solving infinite games with an erm oracle
A Assos, I Attias, Y Dagan, C Daskalakis, MK Fishelson
The Thirty Sixth Annual Conference on Learning Theory, 274-324, 2023
72023
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing
I Attias, GK Dziugaite, M Haghifam, R Livni, DM Roy
Forty-first International Conference on Machine Learning, 2024
3*2024
Agnostic Sample Compression Schemes for Regression
I Attias, S Hanneke, A Kontorovich, M Sadigurschi
Forty-first International Conference on Machine Learning, 2024
2*2024
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss
I Attias, S Hanneke, A Kalavasis, A Karbasi, G Velegkas
The Thirty Seventh Annual Conference on Learning Theory, 359-405, 2024
2024
The Minimax Regret of Sequential Probability Assignment, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
Z Liu, I Attias, DM Roy
ICML 2024 Workshop: Foundations of Reinforcement Learning and Control …, 2024
2024
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
Z Liu, I Attias, DM Roy
Forty-first International Conference on Machine Learning, 2024
2024
Learning revenue maximization using posted prices for stochastic strategic patient buyers
EH Mashiah, I Attias, Y Mansour
Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9090-9098, 2023
2023
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