| 2024 | ICLR | How to Fine-Tune Vision Models with SGD. | Ananya Kumar, Ruoqi Shen, Sbastien Bubeck, Suriya Gunasekar |
| 2023 | ACL | AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation. | Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sbastien Bubeck, Jianfeng Gao |
| 2023 | ALT | On the complexity of finding stationary points of smooth functions in one dimension. | Sinho Chewi, Sbastien Bubeck, Adil Salim |
| 2023 | STOC | The Randomized k-Server Conjecture Is False! | Sbastien Bubeck, Christian Coester, Yuval Rabani |
| 2022 | FOCS | Shortest Paths without a Map, but with an Entropic Regularizer. | Sbastien Bubeck, Christian Coester, Yuval Rabani |
| 2022 | ICML | Data Augmentation as Feature Manipulation. | Ruoqi Shen, Sbastien Bubeck, Suriya Gunasekar |
| 2021 | COLT | Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. | Sbastien Bubeck, Thomas Budzinski, Mark Sellke |
| 2021 | COLT | A Law of Robustness for Two-Layers Neural Networks. | Sbastien Bubeck, Yuanzhi Li, Dheeraj M. Nagaraj |
| 2021 | SODA | Online Multiserver Convex Chasing and Optimization. | Sbastien Bubeck, Yuval Rabani, Mark Sellke |
| 2020 | ALT | First-Order Bayesian Regret Analysis of Thompson Sampling. | Sbastien Bubeck, Mark Sellke |
| 2020 | COLT | Coordination without communication: optimal regret in two players multi-armed bandits. | Sbastien Bubeck, Thomas Budzinski |
| 2020 | COLT | Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. | Sbastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke |
| 2020 | COLT | How to Trap a Gradient Flow. | Sbastien Bubeck, Dan Mikulincer |
| 2020 | FOCS | Entanglement is Necessary for Optimal Quantum Property Testing. | Sbastien Bubeck, Sitan Chen, Jerry Li |
| 2020 | ICML | Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. | Hadrien Hendrikx, Lin Xiao, Sbastien Bubeck, Francis R. Bach, Laurent Massouli |
| 2020 | ICML | Online Learning for Active Cache Synchronization. | Andrey Kolobov, Sbastien Bubeck, Julian Zimmert |
| 2020 | SODA | Chasing Nested Convex Bodies Nearly Optimally. | Sbastien Bubeck, Bo'az Klartag, Yin Tat Lee, Yuanzhi Li, Mark Sellke |
| 2019 | COLT | Near-optimal method for highly smooth convex optimization. | Sbastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford |
| 2019 | COLT | Improved Path-length Regret Bounds for Bandits. | Sbastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei |
| 2019 | COLT | Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives. | Alexander V. Gasnikov, Pavel E. Dvurechensky, Eduard Gorbunov, Evgeniya A. Vorontsova, Daniil Selikhanovych, Csar A. Uribe, Bo Jiang, Haoyue Wang, Shuzhong Zhang, Sbastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford |
| 2019 | ICML | Adversarial examples from computational constraints. | Sbastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn |
| 2019 | SODA | A Nearly-Linear Bound for Chasing Nested Convex Bodies. | C. J. Argue, Sbastien Bubeck, Michael B. Cohen, Anupam Gupta, Yin Tat Lee |
| 2019 | SODA | Metrical task systems on trees via mirror descent and unfair gluing. | Sbastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee |
| 2019 | STOC | Competitively chasing convex bodies. | Sbastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke |
| 2018 | ALT | Sparsity, variance and curvature in multi-armed bandits. | Sbastien Bubeck, Michael B. Cohen, Yuanzhi Li |
| 2018 | COLT | Conference on Learning Theory 2018: Preface. | Sbastien Bubeck, Philippe Rigollet |
| 2018 | ICML | Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits. | Zeyuan Allen-Zhu, Sbastien Bubeck, Yuanzhi Li |
| 2018 | STOC | An homotopy method for l | Sbastien Bubeck, Michael B. Cohen, Yin Tat Lee, Yuanzhi Li |
| 2018 | STOC | k-server via multiscale entropic regularization. | Sbastien Bubeck, Michael B. Cohen, Yin Tat Lee, James R. Lee, Aleksander Madry |
| 2017 | ICML | Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks. | Kevin Scaman, Francis R. Bach, Sbastien Bubeck, Yin Tat Lee, Laurent Massouli |
| 2017 | STOC | Local max-cut in smoothed polynomial time. | Omer Angel, Sbastien Bubeck, Yuval Peres, Fan Wei |
| 2017 | STOC | Kernel-based methods for bandit convex optimization. | Sbastien Bubeck, Yin Tat Lee, Ronen Eldan |
| 2016 | COLT | Multi-scale exploration of convex functions and bandit convex optimization. | Sbastien Bubeck, Ronen Eldan |
| 2016 | ICML | Black-box Optimization with a Politician. | Sbastien Bubeck, Yin Tat Lee |
| 2015 | COLT | Bandit Convex Optimization: \(\sqrt{T}\) Regret in One Dimension. | Sbastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres |
| 2015 | COLT | The entropic barrier: a simple and optimal universal self-concordant barrier. | Sbastien Bubeck, Ronen Eldan |
| 2014 | CISS | Prior-free and prior-dependent regret bounds for Thompson Sampling. | Sbastien Bubeck, Che-Yu Liu |
| 2014 | COLT | lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits. | Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sbastien Bubeck |
| 2014 | COLT | Most Correlated Arms Identification. | Che-Yu Liu, Sbastien Bubeck |
| 2013 | COLT | Bounded regret in stochastic multi-armed bandits. | Sbastien Bubeck, Vianney Perchet, Philippe Rigollet |
| 2013 | ICML | Multiple Identifications in Multi-Armed Bandits. | Sbastien Bubeck, Tengyao Wang, Nitin Viswanathan |
| 2011 | ALT | Lipschitz Bandits without the Lipschitz Constant. | Sbastien Bubeck, Gilles Stoltz, Jia Yuan Yu |
| 2010 | COLT | Best Arm Identification in Multi-Armed Bandits. | Jean-Yves Audibert, Sbastien Bubeck, Rmi Munos |
| 2010 | COLT | Open Loop Optimistic Planning. | Sbastien Bubeck, Rmi Munos |
| 2009 | ALT | Pure Exploration in Multi-armed Bandits Problems. | Sbastien Bubeck, Rmi Munos, Gilles Stoltz |
| 2009 | COLT | Minimax Policies for Adversarial and Stochastic Bandits. | Jean-Yves Audibert, Sbastien Bubeck |