Idan Attias - RankMe

43 papers A* 13A 1B 2Journal 27

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Reduction from Delayed to Immediate Feedback for Online Convex Optimization with Improved Guarantees. CoRR Alexander Ryabchenko, Idan Attias, Daniel M. Roy
2026	J	`jnl`	Positive Distribution Shift as a Framework for Understanding Tractable Learning. CoRR Marko Medvedev, Idan Attias, Elisabetta Cornacchia, Theodor Misiakiewicz, Gal Vardi, Nathan Srebro
2025	A*	`conf`	Capacity-Constrained Online Learning with Delays: Scheduling Frameworks and Regret Trade-offs. COLT Alexander Ryabchenko, Idan Attias, Daniel M. Roy
2025	J	`jnl`	Capacity-Constrained Online Learning with Delays: Scheduling Frameworks and Regret Trade-offs. CoRR Alexander Ryabchenko, Idan Attias, Daniel M. Roy
2025	J	`jnl`	Fixed Point Computation: Beating Brute Force with Smoothed Analysis. CoRR Idan Attias, Yuval Dagan, Constantinos Daskalakis, Rui Yao, Manolis Zampetakis
2025	J	`jnl`	Learning-Augmented Algorithms for Boolean Satisfiability. CoRR Idan Attias, Xing Gao, Lev Reyzin
2025	J	`jnl`	On the Dichotomy Between Privacy and Traceability in ℓ CoRR Sasha Voitovych, Mahdi Haghifam, Idan Attias, Gintare Karolina Dziugaite, Roi Livni, Daniel M. Roy
2025	J	`jnl`	On the Hardness of Learning Regular Expressions. CoRR Idan Attias, Lev Reyzin, Nathan Srebro, Gal Vardi
2025	A*	`conf`	PAC Learning with Improvements. ICML Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew R. Walter
2025	J	`jnl`	PAC Learning with Improvements. CoRR Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew R. Walter
2025	B	`conf`	Sample Compression Scheme Reductions. ALT Idan Attias, Steve Hanneke, Arvind Ramaswami
2025	J	`jnl`	Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning. CoRR Idan Attias, Steve Hanneke, Arvind Ramaswami
2024	J	`jnl`	A Framework for Adversarial Streaming Via Differential Privacy and Difference Estimators. Algorithmica Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
2024	A*	`conf`	Agnostic Sample Compression Schemes for Regression. ICML Idan Attias, Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi
2024	A*	`conf`	Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals. ICML Ziyi Liu, Idan Attias, Daniel M. Roy
2024	J	`jnl`	Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals. CoRR Ziyi Liu, Idan Attias, Daniel M. Roy
2024	J	`jnl`	Fat-Shattering Dimension of k-fold Aggregations. J. Mach. Learn. Res. Idan Attias, Aryeh Kontorovich
2024	J	`jnl`	Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization. CoRR Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
2024	A*	`conf`	Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing. ICML Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
2024	J	`jnl`	Sample Compression Scheme Reductions. CoRR Idan Attias, Steve Hanneke, Arvind Ramaswami
2024	A*	`conf`	Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood. NeurIPS Ziyi Liu, Idan Attias, Dan Roy
2024	J	`jnl`	Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood. CoRR Ziyi Liu, Idan Attias, Daniel M. Roy
2024	A*	`conf`	Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
2023	A	`conf`	A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. ITCS Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
2023	A*	`conf`	Adversarially Robust PAC Learnability of Real-Valued Functions. ICML Idan Attias, Steve Hanneke
2023	A*	`conf`	Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers. AAAI Eitan-Hai Mashiah, Idan Attias, Yishay Mansour
2023	A*	`conf`	Online Learning and Solving Infinite Games with an ERM Oracle. COLT Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell K. Fishelson
2023	J	`jnl`	Online Learning and Solving Infinite Games with an ERM Oracle. CoRR Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson
2023	A*	`conf`	Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
2023	J	`jnl`	Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
2022	A*	`conf`	A Characterization of Semi-Supervised Adversarially Robust PAC Learnability. NeurIPS Idan Attias, Steve Hanneke, Yishay Mansour
2022	J	`jnl`	A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability. CoRR Idan Attias, Steve Hanneke, Yishay Mansour
2022	J	`jnl`	Adversarially Robust Learning of Real-Valued Functions. CoRR Idan Attias, Steve Hanneke
2022	J	`jnl`	Domain Invariant Adversarial Learning. Trans. Mach. Learn. Res. Matan Levi, Idan Attias, Aryeh Kontorovich
2022	J	`jnl`	Improved Generalization Bounds for Adversarially Robust Learning. J. Mach. Learn. Res. Idan Attias, Aryeh Kontorovich, Yishay Mansour
2022	J	`jnl`	Stochastic Strategic Patient Buyers: Revenue maximization using posted prices. CoRR Eitan-Hai Mashiah, Idan Attias, Yishay Mansour
2021	J	`jnl`	A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. CoRR Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
2021	J	`jnl`	Domain Invariant Adversarial Learning. CoRR Matan Levi, Idan Attias, Aryeh Kontorovich
2021	J	`jnl`	Fat-shattering dimension of k-fold maxima. CoRR Aryeh Kontorovich, Idan Attias
2020	A*	`conf`	Prediction with Corrupted Expert Advice. NeurIPS Idan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni
2020	J	`jnl`	Prediction with Corrupted Expert Advice. CoRR Idan Amir, Idan Attias, Tomer Koren, Roi Livni, Yishay Mansour
2019	B	`conf`	Improved Generalization Bounds for Robust Learning. ALT Idan Attias, Aryeh Kontorovich, Yishay Mansour
2018	J	`jnl`	Improved generalization bounds for robust learning. CoRR Idan Attias, Aryeh Kontorovich, Yishay Mansour