Hello!
I am a postdoctoral researcher at the Institute for Data, Econometrics, Algorithms, and Learning (IDEAL) in Chicago, where I am hosted by Lev Reyzin (University of Illinois Chicago) and Avrim Blum (Toyota Technological Institute at Chicago).
I earned my PhD from the Computer Science Department at Ben-Gurion University, where I had the privilege of being advised by Aryeh Kontorovich (Ben-Gurion University) and Yishay Mansour (Tel Aviv University and Google Research).
Prior to that, I completed my Bachelor's degree in Mathematics and Computer Science at Tel Aviv University.
Research interests
Idan Attias
My primary research interests lie in the foundations of machine learning theory and data-driven sequential decision-making, as well as their intersections with game theory, private data analysis, optimization, information theory, and theoretical computer science.
Recent news and activities
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I'll participate in the Deep Learning Theory workshop at the Simons Institute in Berkeley (Feb 2025) and at the Simons Foundation in New York (Sep 2025)
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I’m helping with the organization of FOCS '24 in Chicago, come to the learning session on October 30
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I'll participate in the Rising Stars in Data Science workshop at UCSD (Nov 2024)
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Our paper on "Information Complexity of Stochastic Convex Optimization" won a best paper award at ICML 2024
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I'll start a postdoctoral position in fall '24 at IDEAL Institute (NSF TRIPODS program), hosted by Lev Reyzin (UIC) and Avrim Blum (TTIC)
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I'll be at Vector Institute to work with Daniel Roy and Karolina Dziugaite as a research intern starting August '23
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Received the Friedman Award for outstanding research achievements
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Visiting Archimedes AI in Athena Research and Innovation Center (Jul 2022)
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Awarded the Kreitman Dean's List for PhD Students, 2021/2022 (top 5%)
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Visiting the Learning and Games program at Simon’s Institute (Jan-Mar 2022)
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Received the Israeli Council of Higher Education scholarship (VATAT) for outstanding PhD students in data science
Preprints
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Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
Idan Attias, Steve Hanneke, Arvind Ramaswami
Idan Attias, Xing Gao, Lev Reyzin
Idan Attias, Yuval Dagan, Constantinos Daskalakis, Rui Yao, Manolis Zampetakis
Sasha Voitovych, Mahdi Haghifam, Idan Attias, Gintare Karolina Dziugaite, Roi Livni, Daniel M. Roy
Arxiv
6th Annual Symposium on Foundations of Responsible Computing (FORC 2025), Highlights Track
Alexander Ryabchenko, Idan Attias, Daniel M. Roy
38th Annual Conference on Learning Theory (COLT 2025)
Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma, Matthew Walter
42th International Conference on Machine Learning (ICML 2025)
Publications
Idan Attias, Steve Hanneke, Arvind Ramaswami
36th International Conference on Algorithmic Learning Theory (ALT 2025)
Ziyi Liu, Idan Attias, Daniel M. Roy
38th Annual Conference on Neural Information Processing Systems (Neurips 2024)
Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy
41th International Conference on Machine Learning ICML 2024 Oral
ICML 2024 Best Paper Award
Idan Attias, Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi
41th International Conference on Machine Learning ICML 2024 Spotlight
Arxiv
Ziyi Liu, Idan Attias, Daniel M. Roy
41th International Conference on Machine Learning ICML 2024
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
37th Annual Conference on Learning Theory COLT 2024
Idan Attias, Aryeh Kontorovich
Journal of Machine Learning Research, Vol. 25 JMLR 2024
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
37th Annual Conference on Neural Information Processing Systems NeurIPS 2023 Oral
Angelos Assos, Idan Attias, Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson
36th Annual Conference on Learning Theory COLT 2023
Idan Attias, Steve Hanneke
40th International Conference on Machine Learning ICML 2023
Eitan-Hai Mashiah, Idan Attias, Yishay Mansour
37th Conference on Artificial Intelligence AAAI 2023 Oral
Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
14th Innovations in Theoretical Computer Science ITCS 2023
Idan Attias, Steve Hanneke, Yishay Mansour
36th Annual Conference on Neural Information Processing Systems NeurIPS 2022
Matan Levi, Idan Attias, Aryeh Kontorovich
Transactions on Machine Learning Research TMLR 2022
Idan Amir, Idan Attias, Tomer Koren, Roi Livni, Yishay Mansour
34th Annual Conference on Neural Information Processing Systems NeurIPS 2020 Spotlight
Idan Attias, Aryeh Kontorovich, Yishay Mansour
Journal of Machine Learning Research, Vol. 23 JMLR 2022
Preliminary version: 30th International Conference on Algorithmic Learning Theory ALT 2019
Authors are listed in alphabetical order, except sometimes when a student author is listed first
Service
Routinely I serve as a reviewer at the conferences NeurIPS, ICML, COLT, AISTATS, ALT, AAAI, and the journals JMLR and TMLR.
Teaching
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Introduction to Machine Learning, Ben-Gurion University
Teaching Assistant: Fall 23
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Computational Models, Ben-Gurion University
Teaching Assistant: Spring 20, Spring 21, Spring 22, Spring 23
[Regular languages and finite automata, Grammars and Context-Free Languages, Turing Machines and Computability, Introduction to complexity]
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Design of Algorithms, Ben-Gurion University
Teaching Assistant: Fall 21, Fall 22
[Reductions, Greedy algorithms, Dynamic programming, Shortest path, Maximum flow, Randomized algorithms, Linear programming, Approximation algorithms]
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Theory of Interactive Learning (graduate-level course), Ben-Gurion University
Grader: Spring 22
[PAC learning, VC theory, Active learning]
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Introduction to Computer Science, Ben-Gurion University
Teaching Assistant: Fall 20
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Discrete Math, Tel Aviv University
Grader: Fall 16
Contact
>>> Email = "idanattias88"+chr(64)+".".join(["gmail","com"])
University of Illinois at Chicago — Science and Engineering Offices (MC 249), Room 618, Department of Mathematics, Statistics, and Computer Science
Toyota Technological Institute at Chicago — Room 527