Bubeck, Sébastien

61 publications

ICLR 2024 How to Fine-Tune Vision Models with SGD Ananya Kumar, Ruoqi Shen, Sebastien Bubeck, Suriya Gunasekar

NeurIPS 2023 Learning Threshold Neurons via Edge of Stability Kwangjun Ahn, Sebastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang

ALT 2023 On the Complexity of Finding Stationary Points of Smooth Functions in One Dimension Sinho Chewi, Sébastien Bubeck, Adil Salim

NeurIPSW 2023 TinyGSM: Achieving 80% on GSM8k with One Billion Parameters Bingbin Liu, Sebastien Bubeck, Ronen Eldan, Janardhan Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang

ICML 2022 Data Augmentation as Feature Manipulation Ruoqi Shen, Sebastien Bubeck, Suriya Gunasekar

NeurIPS 2022 LiteTransformerSearch: Training-Free Neural Architecture Search for Efficient Language Models Mojan Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio Cesar Teodoro Mendes, Sebastien Bubeck, Farinaz Koushanfar, Debadeepta Dey

COLT 2021 A Law of Robustness for Two-Layers Neural Networks Sebastien Bubeck, Yuanzhi Li, Dheeraj M Nagaraj

NeurIPS 2021 A Single Gradient Step Finds Adversarial Examples on Random Two-Layers Neural Networks Sebastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes

NeurIPS 2021 A Universal Law of Robustness via Isoperimetry Sebastien Bubeck, Mark Sellke

NeurIPS 2021 Adversarial Examples in Multi-Layer Random ReLU Networks Peter L. Bartlett, Sebastien Bubeck, Yeshwanth Cherapanamjeri

COLT 2021 Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret with Neither Communication nor Collisions Sebastien Bubeck, Thomas Budzinski, Mark Sellke

ICMLW 2021 Ranking Architectures by Feature Extraction Capabilities Debadeepta Dey, Shital Shah, Sebastien Bubeck

COLT 2020 Coordination Without Communication: Optimal Regret in Two Players Multi-Armed Bandits Sébastien Bubeck, Thomas Budzinski

ALT 2020 First-Order Bayesian Regret Analysis of Thompson Sampling Sébastien Bubeck, Mark Sellke

COLT 2020 How to Trap a Gradient Flow Sébastien Bubeck, Dan Mikulincer

NeurIPS 2020 Network Size and Size of the Weights in Memorization with Two-Layers Neural Networks Sebastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer

COLT 2020 Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate with Collision Information, Sublinear Without Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke

ICML 2020 Online Learning for Active Cache Synchronization Andrey Kolobov, Sebastien Bubeck, Julian Zimmert

ICML 2020 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulie

ICML 2019 Adversarial Examples from Computational Constraints Sebastien Bubeck, Yin Tat Lee, Eric Price, Ilya Razenshteyn

NeurIPS 2019 Complexity of Highly Parallel Non-Smooth Convex Optimization Sebastien Bubeck, Qijia Jiang, Yin-Tat Lee, Yuanzhi Li, Aaron Sidford

COLT 2019 Improved Path-Length Regret Bounds for Bandits Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei

JMLR 2019 Multi-Scale Online Learning: Theory and Applications to Online Auctions and Pricing Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang, Rad Niazadeh

COLT 2019 Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-Th Derivatives Alexander Gasnikov, Pavel Dvurechensky, Eduard Gorbunov, Evgeniya Vorontsova, Daniil Selikhanovych, César A. Uribe, Bo Jiang, Haoyue Wang, Shuzhong Zhang, Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford

COLT 2019 Near-Optimal Method for Highly Smooth Convex Optimization Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford

JMLR 2019 Optimal Convergence Rates for Convex Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié

NeurIPS 2019 Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman, Jerry Li, Ilya Razenshteyn, Pengchuan Zhang, Huan Zhang, Sebastien Bubeck, Greg Yang

COLT 2018 Conference on Learning Theory 2018: Preface Sébastien Bubeck, Philippe Rigollet

COLT 2018 Conference on Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018 Sébastien Bubeck, Vianney Perchet, Philippe Rigollet

NeurIPS 2018 Is Q-Learning Provably Efficient? Chi Jin, Zeyuan Allen-Zhu, Sebastien Bubeck, Michael I Jordan

ICML 2018 Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits Zeyuan Allen-Zhu, Sebastien Bubeck, Yuanzhi Li

NeurIPS 2018 Optimal Algorithms for Non-Smooth Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sebastien Bubeck, Laurent Massoulié, Yin Tat Lee

ALT 2018 Sparsity, Variance and Curvature in Multi-Armed Bandits Sébastien Bubeck, Michael Cohen, Yuanzhi Li

ICML 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié

ICML 2016 Black-Box Optimization with a Politician Sebastien Bubeck, Yin Tat Lee

COLT 2016 Multi-Scale Exploration of Convex Functions and Bandit Convex Optimization Sébastien Bubeck, Ronen Eldan

COLT 2015 Bandit Convex Optimization: \(\sqrt{T}\) Regret in One Dimension Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres

FnTML 2015 Convex Optimization: Algorithms and Complexity Sébastien Bubeck

JMLR 2015 Exceptional Rotations of Random Graphs: A VC Theory Louigi Addario-Berry, Shankar Bhamidi, Sébastien Bubeck, Luc Devroye, Gábor Lugosi, Roberto Imbuzeiro Oliveira

NeurIPS 2015 Finite-Time Analysis of Projected Langevin Monte Carlo Sebastien Bubeck, Ronen Eldan, Joseph Lehec

COLT 2015 The Entropic Barrier: A Simple and Optimal Universal Self-Concordant Barrier Sébastien Bubeck, Ronen Eldan

COLT 2014 Lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits Kevin G. Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck

COLT 2014 Most Correlated Arms Identification Che-Yu Liu, Sébastien Bubeck

COLT 2013 Bounded Regret in Stochastic Multi-Armed Bandits Sébastien Bubeck, Vianney Perchet, Philippe Rigollet

JMLR 2013 Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality Sébastien Bubeck, Damien Ernst, Aurélien Garivier

NeurIPS 2013 Prior-Free and Prior-Dependent Regret Bounds for Thompson Sampling Sebastien Bubeck, Che-Yu Liu

FnTML 2012 Regret Analysis of Stochastic and Nonstochastic Multi-Armed Bandit Problems Sébastien Bubeck, Nicolò Cesa-Bianchi

COLT 2012 The Best of Both Worlds: Stochastic and Adversarial Bandits Sébastien Bubeck, Aleksandrs Slivkins

COLT 2012 Towards Minimax Policies for Online Linear Optimization with Bandit Feedback Sébastien Bubeck, Nicoló Cesa-Bianchi, Sham M. Kakade

ALT 2011 Lipschitz Bandits Without the Lipschitz Constant Sébastien Bubeck, Gilles Stoltz, Jia Yuan Yu

COLT 2011 Minimax Policies for Combinatorial Prediction Games Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi

NeurIPS 2011 Multi-Bandit Best Arm Identification Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric, Sébastien Bubeck

JMLR 2011 X-Armed Bandits Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári

COLT 2010 Best Arm Identification in Multi-Armed Bandits Jean-Yves Audibert, Sébastien Bubeck, Rémi Munos

COLT 2010 Open Loop Optimistic Planning Sébastien Bubeck, Rémi Munos

JMLR 2010 Regret Bounds and Minimax Policies Under Partial Monitoring Jean-Yves Audibert, Sébastien Bubeck

COLT 2009 Minimax Policies for Adversarial and Stochastic Bandits Jean-Yves Audibert, Sébastien Bubeck

JMLR 2009 Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions Sébastien Bubeck, Ulrike von Luxburg

ALT 2009 Pure Exploration in Multi-Armed Bandits Problems Sébastien Bubeck, Rémi Munos, Gilles Stoltz

NeurIPS 2008 Online Optimization in X-Armed Bandits Sébastien Bubeck, Gilles Stoltz, Csaba Szepesvári, Rémi Munos

NeurIPS 2007 Consistent Minimization of Clustering Objective Functions Ulrike V. Luxburg, Stefanie Jegelka, Michael Kaufmann, Sébastien Bubeck