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Idan Attias
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2020 – today
- 2024
- [j3]Idan Attias, Aryeh Kontorovich:
Fat-Shattering Dimension of k-fold Aggregations. J. Mach. Learn. Res. 25: 144:1-144:29 (2024) - [c12]Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT 2024: 359-405 - [c11]Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy:
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing. ICML 2024 - [c10]Idan Attias, Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi:
Agnostic Sample Compression Schemes for Regression. ICML 2024 - [c9]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. ICML 2024 - [i12]Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy:
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization. CoRR abs/2402.09327 (2024) - [i11]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 abs/2407.00950 (2024) - 2023
- [c8]Eitan-Hai Mashiah, Idan Attias, Yishay Mansour:
Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers. AAAI 2023: 9090-9098 - [c7]Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell K. Fishelson:
Online Learning and Solving Infinite Games with an ERM Oracle. COLT 2023: 274-324 - [c6]Idan Attias, Steve Hanneke:
Adversarially Robust PAC Learnability of Real-Valued Functions. ICML 2023: 1172-1199 - [c5]Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer:
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. ITCS 2023: 8:1-8:19 - [c4]Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS 2023 - [i10]Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson:
Online Learning and Solving Infinite Games with an ERM Oracle. CoRR abs/2307.01689 (2023) - [i9]Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas:
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR abs/2307.03848 (2023) - 2022
- [j2]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved Generalization Bounds for Adversarially Robust Learning. J. Mach. Learn. Res. 23: 175:1-175:31 (2022) - [j1]Matan Levi, Idan Attias, Aryeh Kontorovich:
Domain Invariant Adversarial Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c3]Idan Attias, Steve Hanneke, Yishay Mansour:
A Characterization of Semi-Supervised Adversarially Robust PAC Learnability. NeurIPS 2022 - [i8]Idan Attias, Steve Hanneke, Yishay Mansour:
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability. CoRR abs/2202.05420 (2022) - [i7]Eitan-Hai Mashiah, Idan Attias, Yishay Mansour:
Stochastic Strategic Patient Buyers: Revenue maximization using posted prices. CoRR abs/2202.06143 (2022) - [i6]Idan Attias, Steve Hanneke:
Adversarially Robust Learning of Real-Valued Functions. CoRR abs/2206.12977 (2022) - 2021
- [i5]Matan Levi, Idan Attias, Aryeh Kontorovich:
Domain Invariant Adversarial Learning. CoRR abs/2104.00322 (2021) - [i4]Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer:
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. CoRR abs/2107.14527 (2021) - [i3]Aryeh Kontorovich, Idan Attias:
Fat-shattering dimension of k-fold maxima. CoRR abs/2110.04763 (2021) - 2020
- [c2]Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni:
Prediction with Corrupted Expert Advice. NeurIPS 2020 - [i2]Idan Amir, Idan Attias, Tomer Koren, Roi Livni, Yishay Mansour:
Prediction with Corrupted Expert Advice. CoRR abs/2002.10286 (2020)
2010 – 2019
- 2019
- [c1]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved Generalization Bounds for Robust Learning. ALT 2019: 162-183 - 2018
- [i1]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved generalization bounds for robust learning. CoRR abs/1810.02180 (2018)
Coauthor Index
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last updated on 2024-09-18 00:16 CEST by the dblp team
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