Sebastien Bubeck

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Yin Tat LeePaul G. Allen School of Computer Science & Engineering, University of WashingtonVerified email at uw.edu
Ronen EldanWeizmann InstituteVerified email at weizmann.ac.il
Yuanzhi LiAssistant Professor at CMUVerified email at andrew.cmu.edu
Yi ZhangSenior Researcher at Microsoft Research RedmondVerified email at microsoft.com
Rémi MunosGoogle DeepMindVerified email at inria.fr
Gilles StoltzCNRS / Université Paris-Saclay / HEC ParisVerified email at hec.fr
Eric HorvitzMicrosoftVerified email at microsoft.com
Hamid PalangiGoogle and University of WashingtonVerified email at google.com
Marco Tulio RibeiroGoogle DeepMindVerified email at cs.washington.edu
Harsha NoriMicrosoft ResearchVerified email at microsoft.com
Scott LundbergGoogle DeepMindVerified email at google.com
Ece KamarMicrosoft ResearchVerified email at microsoft.com
Varun ChandrasekaranUniversity of Illinois Urbana-ChampaignVerified email at illinois.edu
Gabor LugosiICREA and Universitat Pompeu FabraVerified email at upf.edu
Nicolò Cesa-BianchiProfessor of Computer Science, Università degli Studi di Milano and Politecnico di MilanoVerified email at unimi.it
Mark SellkeAssistant Professor of Statistics, Harvard UniversityVerified email at fas.harvard.edu
Suriya GunasekarMSR RedmondVerified email at ttic.edu
Shital ShahMicrosoft ResearchVerified email at microsoft.com
Mojan JavaheripiSenior Researcher, Microsoft ResearchVerified email at microsoft.com
Laurent MassoulieInria, MSR-Inria Joint CentreVerified email at inria.fr

Sebastien Bubeck

VP AI and Distinguished Scientist, Microsoft

Verified email at microsoft.com - Homepage

machine learning theoretical computer science convex optimization multi-armed bandits


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Regret analysis of stochastic and nonstochastic multi-armed bandit problems S Bubeck, N Cesa-Bianchi Foundations and Trends in Machine Learning 5, 1-122, 2012	3185	2012
Sparks of artificial general intelligence: Early experiments with gpt-4 S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ... arXiv preprint arXiv:2303.12712, 2023	3103	2023
Convex optimization: Algorithms and complexity S Bubeck Foundations and Trends in Machine Learning 8, 231-357, 2014	2503	2014
Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine P Lee, S Bubeck, J Petro New England Journal of Medicine 388 (13), 1233-1239, 2023	1032	2023
Is Q-learning provably efficient? C Jin, Z Allen-Zhu, S Bubeck, MI Jordan Advances in neural information processing systems 31, 2018	971	2018
Best arm identification in multi-armed bandits JY Audibert, S Bubeck, R Munos COLT 2010, 2010	953	2010
Pure exploration in multi-armed bandits problems S Bubeck, R Munos, G Stoltz Algorithmic Learning Theory, 23-37, 2009	618	2009
Provably robust deep learning via adversarially trained smoothed classifiers H Salman, J Li, I Razenshteyn, P Zhang, H Zhang, S Bubeck, G Yang Advances in neural information processing systems 32, 2019	583	2019
X-armed bandits S Bubeck, R Munos, G Stoltz, C Szepesvári Journal of Machine Learning Research 12, 1587-1627, 2011	509	2011
Minimax policies for adversarial and stochastic bandits JY Audibert, S Bubeck COLT 2009, 2009	501	2009
lil'UCB: An Optimal Exploration Algorithm for Multi-Armed Bandits K Jamieson, M Malloy, R Nowak, S Bubeck COLT 2014, 2013	486	2013
Textbooks are all you need S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ... arXiv preprint arXiv:2306.11644, 2023	382	2023
Optimal algorithms for smooth and strongly convex distributed optimization in networks K Scaman, F Bach, S Bubeck, YT Lee, L Massoulié international conference on machine learning, 3027-3036, 2017	363	2017
Bandits with heavy tail S Bubeck, N Cesa-Bianchi, G Lugosi IEEE Transactions on Information Theory 59 (11), 7711-7717, 2013	324	2013
Pure exploration in finitely-armed and continuous-armed bandits S Bubeck, R Munos, G Stoltz Theoretical Computer Science 412, 1832-1852, 2010	320	2010
Online Optimization in X-Armed Bandits S Bubeck, G Stoltz, C Szepesvári, R Munos Advances in Neural Information Processing Systems 21, 201-208, 2008	276	2008
Regret bounds and minimax policies under partial monitoring JY Audibert, S Bubeck The Journal of Machine Learning Research 11, 2635-2686, 2010	275	2010
Phi-3 technical report: A highly capable language model locally on your phone M Abdin, SA Jacobs, AA Awan, J Aneja, A Awadallah, H Awadalla, ... arXiv preprint arXiv:2404.14219, 2024	274	2024
Textbooks are all you need ii: phi-1.5 technical report Y Li, S Bubeck, R Eldan, A Del Giorno, S Gunasekar, YT Lee arXiv preprint arXiv:2309.05463, 2023	273	2023
The best of both worlds: Stochastic and adversarial bandits S Bubeck, A Slivkins COLT 2012, 2012	272	2012

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