Sébastien Bubeck

171 papers A* 53A 1B 5Misc 1Journal 102Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Early science acceleration experiments with GPT-5. CoRR Sébastien Bubeck, Christian Coester, Ronen Eldan, Timothy Gowers, Yin Tat Lee, Alexandru Lupsasca, Mehtaab Sawhney, Robert Scherrer, Mark Sellke, Brian K. Spears, Derya Unutmaz, Kevin Weil, Steven Yin, Nikita Zhivotovskiy
2025	J	`jnl`	Shortest Paths Without a Map, but with an Entropic Regularizer. SIAM J. Comput. Sébastien Bubeck, Christian Coester, Yuval Rabani
2024	A*	`conf`	How to Fine-Tune Vision Models with SGD. ICLR Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
2024	J	`jnl`	How to Trap a Gradient Flow. SIAM J. Comput. Sébastien Bubeck, Dan Mikulincer
2024	J	`jnl`	Phi-4 Technical Report. CoRR Marah I Abdin, Jyoti Aneja, Harkirat S. Behl, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Michael Harrison, Russell J. Hewett, Mojan Javaheripi, Piero Kauffmann, James R. Lee, Yin Tat Lee, Yuanzhi Li, Weishung Liu, Caio C. T. Mendes, Anh Nguyen, Eric Price, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Xin Wang, Rachel Ward, Yue Wu, Dingli Yu, Cyril Zhang, Yi Zhang
2024	J	`jnl`	Small Language Models for Application Interactions: A Case Study. CoRR Beibin Li, Yi Zhang, Sébastien Bubeck, Jeevan Pathuri, Ishai Menache
2023	J	`jnl`	A Universal Law of Robustness via Isoperimetry. J. ACM Sébastien Bubeck, Mark Sellke
2023	—	`conf`	AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation. ACL (Findings) Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao
2023	J	`jnl`	First-Order Bayesian Regret Analysis of Thompson Sampling. IEEE Trans. Inf. Theory Sébastien Bubeck, Mark Sellke
2023	A*	`conf`	Learning threshold neurons via edge of stability. NeurIPS Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
2023	B	`conf`	On the complexity of finding stationary points of smooth functions in one dimension. ALT Sinho Chewi, Sébastien Bubeck, Adil Salim
2023	J	`jnl`	Positional Description Matters for Transformers Arithmetic. CoRR Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Yuanzhi Li, Yi Zhang
2023	J	`jnl`	Sparks of Artificial General Intelligence: Early experiments with GPT-4. CoRR Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, Yi Zhang
2023	J	`jnl`	Textbooks Are All You Need II: phi-1.5 technical report. CoRR Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, Allie Del Giorno, Suriya Gunasekar, Yin Tat Lee
2023	J	`jnl`	Textbooks Are All You Need. CoRR Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li
2023	A*	`conf`	The Randomized k-Server Conjecture Is False! STOC Sébastien Bubeck, Christian Coester, Yuval Rabani
2023	J	`jnl`	TinyGSM: achieving >80% on GSM8k with small language models. CoRR Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang
2022	J	`jnl`	AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers. CoRR Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao
2022	A*	`conf`	Data Augmentation as Feature Manipulation. ICML Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
2022	J	`jnl`	Data Augmentation as Feature Manipulation: a story of desert cows and grass cows. CoRR Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
2022	J	`jnl`	How to Fine-Tune Vision Models with SGD. CoRR Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
2022	J	`jnl`	Learning threshold neurons via the "edge of stability". CoRR Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
2022	A*	`conf`	LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models. NeurIPS Mojan Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio César Teodoro Mendes, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey
2022	J	`jnl`	LiteTransformerSearch: Training-free On-device Search for Efficient Autoregressive Language Models. CoRR Mojan Javaheripi, Shital Shah, Subhabrata Mukherjee, Tomasz L. Religa, Caio C. T. Mendes, Gustavo H. de Rosa, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey
2022	A*	`conf`	Shortest Paths without a Map, but with an Entropic Regularizer. FOCS Sébastien Bubeck, Christian Coester, Yuval Rabani
2022	J	`jnl`	Shortest Paths without a Map, but with an Entropic Regularizer. CoRR Sébastien Bubeck, Christian Coester, Yuval Rabani
2022	J	`jnl`	The Randomized k-Server Conjecture is False! CoRR Sébastien Bubeck, Christian Coester, Yuval Rabani
2022	J	`jnl`	Unveiling Transformers with LEGO: a synthetic reasoning task. CoRR Yi Zhang, Arturs Backurs, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Tal Wagner
2021	A*	`conf`	A Law of Robustness for Two-Layers Neural Networks. COLT Sébastien Bubeck, Yuanzhi Li, Dheeraj M. Nagaraj
2021	A*	`conf`	A Universal Law of Robustness via Isoperimetry. NeurIPS Sébastien Bubeck, Mark Sellke
2021	J	`jnl`	A Universal Law of Robustness via Isoperimetry. CoRR Sébastien Bubeck, Mark Sellke
2021	A*	`conf`	A single gradient step finds adversarial examples on random two-layers neural networks. NeurIPS Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
2021	J	`jnl`	A single gradient step finds adversarial examples on random two-layers neural networks. CoRR Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Rémi Tachet des Combes
2021	A*	`conf`	Adversarial Examples in Multi-Layer Random ReLU Networks. NeurIPS Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri
2021	J	`jnl`	Adversarial Examples in Multi-Layer Random ReLU Networks. CoRR Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri
2021	A*	`conf`	Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. COLT Sébastien Bubeck, Thomas Budzinski, Mark Sellke
2021	J	`jnl`	FEAR: A Simple Lightweight Method to Rank Architectures. CoRR Debadeepta Dey, Shital Shah, Sébastien Bubeck
2021	J	`jnl`	Kernel-based Methods for Bandit Convex Optimization. J. ACM Sébastien Bubeck, Ronen Eldan, Yin Tat Lee
2021	A	`conf`	Metrical Service Systems with Transformations. ITCS Sébastien Bubeck, Niv Buchbinder, Christian Coester, Mark Sellke
2021	J	`jnl`	Metrical Task Systems on Trees via Mirror Descent and Unfair Gluing. SIAM J. Comput. Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee
2021	A*	`conf`	Online Multiserver Convex Chasing and Optimization. SODA Sébastien Bubeck, Yuval Rabani, Mark Sellke
2020	J	`jnl`	A law of robustness for two-layers neural networks. CoRR Sébastien Bubeck, Yuanzhi Li, Dheeraj Nagaraj
2020	A*	`conf`	Chasing Nested Convex Bodies Nearly Optimally. SODA Sébastien Bubeck, Bo'az Klartag, Yin Tat Lee, Yuanzhi Li, Mark Sellke
2020	J	`jnl`	Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. CoRR Sébastien Bubeck, Thomas Budzinski, Mark Sellke
2020	A*	`conf`	Coordination without communication: optimal regret in two players multi-armed bandits. COLT Sébastien Bubeck, Thomas Budzinski
2020	J	`jnl`	Coordination without communication: optimal regret in two players multi-armed bandits. CoRR Sébastien Bubeck, Thomas Budzinski
2020	A*	`conf`	Entanglement is Necessary for Optimal Quantum Property Testing. FOCS Sébastien Bubeck, Sitan Chen, Jerry Li
2020	J	`jnl`	Entanglement is Necessary for Optimal Quantum Property Testing. CoRR Sébastien Bubeck, Sitan Chen, Jerry Li
2020	B	`conf`	First-Order Bayesian Regret Analysis of Thompson Sampling. ALT Sébastien Bubeck, Mark Sellke
2020	A*	`conf`	How to Trap a Gradient Flow. COLT Sébastien Bubeck, Dan Mikulincer
2020	J	`jnl`	How to trap a gradient flow. CoRR Sébastien Bubeck, Dan Mikulincer
2020	J	`jnl`	Metrical Service Systems with Transformations. CoRR Sébastien Bubeck, Niv Buchbinder, Christian Coester, Mark Sellke
2020	A*	`conf`	Network size and size of the weights in memorization with two-layers neural networks. NeurIPS Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
2020	J	`jnl`	Network size and weights size for memorization with two-layers neural networks. CoRR Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
2020	A*	`conf`	Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. COLT Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke
2020	A*	`conf`	Online Learning for Active Cache Synchronization. ICML Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
2020	J	`jnl`	Online Learning for Active Cache Synchronization. CoRR Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
2020	J	`jnl`	Online Multiserver Convex Chasing and Optimization. CoRR Sébastien Bubeck, Yuval Rabani, Mark Sellke
2020	—	`conf`	Parametrized Metrical Task Systems. APPROX-RANDOM Sébastien Bubeck, Yuval Rabani
2020	A*	`conf`	Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. ICML Hadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié
2020	J	`jnl`	Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. CoRR Hadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié
2019	A*	`conf`	A Nearly-Linear Bound for Chasing Nested Convex Bodies. SODA C. J. Argue, Sébastien Bubeck, Michael B. Cohen, Anupam Gupta, Yin Tat Lee
2019	A*	`conf`	Adversarial examples from computational constraints. ICML Sébastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn
2019	J	`jnl`	Competitively Chasing Convex Bodies. SIAM J. Comput. Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
2019	A*	`conf`	Competitively chasing convex bodies. STOC Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
2019	A*	`conf`	Complexity of Highly Parallel Non-Smooth Convex Optimization. NeurIPS Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
2019	J	`jnl`	Complexity of Highly Parallel Non-Smooth Convex Optimization. CoRR Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
2019	J	`jnl`	First-Order Regret Analysis of Thompson Sampling. CoRR Sébastien Bubeck, Mark Sellke
2019	A*	`conf`	Improved Path-length Regret Bounds for Bandits. COLT Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei
2019	J	`jnl`	Improved Path-length Regret Bounds for Bandits. CoRR Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei
2019	A*	`conf`	Metrical task systems on trees via mirror descent and unfair gluing. SODA Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee
2019	J	`jnl`	Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing. J. Mach. Learn. Res. Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang, Rad Niazadeh
2019	A*	`conf`	Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives. COLT Alexander V. Gasnikov, Pavel E. Dvurechensky, Eduard Gorbunov, Evgeniya A. Vorontsova, Daniil Selikhanovych, César A. Uribe, Bo Jiang, Haoyue Wang, Shuzhong Zhang, Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
2019	A*	`conf`	Near-optimal method for highly smooth convex optimization. COLT Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
2019	J	`jnl`	Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. CoRR Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke
2019	J	`jnl`	Optimal Convergence Rates for Convex Distributed Optimization in Networks. J. Mach. Learn. Res. Kevin Scaman, Francis R. Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié
2019	J	`jnl`	Parametrized Metrical Task Systems. CoRR Sébastien Bubeck, Yuval Rabani
2019	A*	`conf`	Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. NeurIPS Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang
2019	J	`jnl`	Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. CoRR Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya P. Razenshteyn, Sébastien Bubeck
2019	J	`jnl`	The Entropic Barrier: Exponential Families, Log-Concave Geometry, and Self-Concordance. Math. Oper. Res. Sébastien Bubeck, Ronen Eldan
2018	J	`jnl`	A Nearly-Linear Bound for Chasing Nested Convex Bodies. CoRR C. J. Argue, Sébastien Bubeck, Michael B. Cohen, Anupam Gupta, Yin Tat Lee
2018	J	`jnl`	Adversarial Examples from Cryptographic Pseudo-Random Generators. CoRR Sébastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn
2018	J	`jnl`	Adversarial examples from computational constraints. CoRR Sébastien Bubeck, Eric Price, Ilya P. Razenshteyn
2018	A*	`conf`	An homotopy method for l STOC Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, Yuanzhi Li
2018	J	`jnl`	Chasing Nested Convex Bodies Nearly Optimally. CoRR Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
2018	J	`jnl`	Competitively Chasing Convex Bodies. CoRR Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
2018	A*	`ed.`	Conference On Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018. COLT Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
2018	A*	`conf`	Conference on Learning Theory 2018: Preface. COLT Sébastien Bubeck, Philippe Rigollet
2018	A*	`conf`	Is Q-Learning Provably Efficient? NeurIPS Chi Jin, Zeyuan Allen-Zhu, Sébastien Bubeck, Michael I. Jordan
2018	J	`jnl`	Is Q-learning Provably Efficient? CoRR Chi Jin, Zeyuan Allen-Zhu, Sébastien Bubeck, Michael I. Jordan
2018	A*	`conf`	Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits. ICML Zeyuan Allen-Zhu, Sébastien Bubeck, Yuanzhi Li
2018	J	`jnl`	Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits. CoRR Zeyuan Allen-Zhu, Sébastien Bubeck, Yuanzhi Li
2018	J	`jnl`	Metrical task systems on trees via mirror descent and unfair gluing. CoRR Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee
2018	A*	`conf`	Optimal Algorithms for Non-Smooth Distributed Optimization in Networks. NeurIPS Kevin Scaman, Francis R. Bach, Sébastien Bubeck, Laurent Massoulié, Yin Tat Lee
2018	J	`jnl`	Sampling from a Log-Concave Distribution with Projected Langevin Monte Carlo. Discret. Comput. Geom. Sébastien Bubeck, Ronen Eldan, Joseph Lehec
2018	B	`conf`	Sparsity, variance and curvature in multi-armed bandits. ALT Sébastien Bubeck, Michael B. Cohen, Yuanzhi Li
2018	A*	`conf`	k-server via multiscale entropic regularization. STOC Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, James R. Lee, Aleksander Madry
2017	J	`jnl`	An homotopy method for 𝓵 CoRR Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, Yuanzhi Li
2017	J	`jnl`	Finding Adam in random growing trees. Random Struct. Algorithms Sébastien Bubeck, Luc Devroye, Gábor Lugosi
2017	A*	`conf`	Kernel-based methods for bandit convex optimization. STOC Sébastien Bubeck, Yin Tat Lee, Ronen Eldan
2017	A*	`conf`	Local max-cut in smoothed polynomial time. STOC Omer Angel, Sébastien Bubeck, Yuval Peres, Fan Wei
2017	A*	`conf`	Online Auctions and Multi-scale Online Learning. EC Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang, Rad Niazadeh
2017	J	`jnl`	Online Auctions and Multi-scale Online Learning. CoRR Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang, Rad Niazadeh
2017	A*	`conf`	Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks. ICML Kevin Scaman, Francis R. Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié
2017	J	`jnl`	Sparsity, variance and curvature in multi-armed bandits. CoRR Sébastien Bubeck, Michael B. Cohen, Yuanzhi Li
2017	J	`jnl`	k-server via multiscale entropic regularization. CoRR Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee, Aleksander Madry
2016	J	`jnl`	Basic models and questions in statistical network analysis. CoRR Miklós Z. Rácz, Sébastien Bubeck
2016	A*	`conf`	Black-box Optimization with a Politician. ICML Sébastien Bubeck, Yin Tat Lee
2016	J	`jnl`	Black-box optimization with a politician. CoRR Sébastien Bubeck, Yin Tat Lee
2016	J	`jnl`	Kernel-based methods for bandit convex optimization. CoRR Sébastien Bubeck, Ronen Eldan, Yin Tat Lee
2016	J	`jnl`	Local max-cut in smoothed polynomial time. CoRR Omer Angel, Sébastien Bubeck, Yuval Peres, Fan Wei
2016	A*	`conf`	Multi-scale exploration of convex functions and bandit convex optimization. COLT Sébastien Bubeck, Ronen Eldan
2016	J	`jnl`	On the Local Profiles of Trees. J. Graph Theory Sébastien Bubeck, Nati Linial
2016	J	`jnl`	Testing for high-dimensional geometry in random graphs. Random Struct. Algorithms Sébastien Bubeck, Jian Ding, Ronen Eldan, Miklós Z. Rácz
2015	J	`jnl`	A geometric alternative to Nesterov's accelerated gradient descent. CoRR Sébastien Bubeck, Yin Tat Lee, Mohit Singh
2015	A*	`conf`	Bandit Convex Optimization: $\sqrt{T}$ Regret in One Dimension. COLT Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres
2015	J	`jnl`	Bandit Convex Optimization: sqrt{T} Regret in One Dimension. CoRR Sébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres
2015	J	`jnl`	Convex Optimization: Algorithms and Complexity. Found. Trends Mach. Learn. Sébastien Bubeck
2015	J	`jnl`	Entropic CLT and phase transition in high-dimensional Wishart matrices. CoRR Sébastien Bubeck, Shirshendu Ganguly
2015	J	`jnl`	Exceptional rotations of random graphs: a VC theory. J. Mach. Learn. Res. Louigi Addario-Berry, Shankar Bhamidi, Sébastien Bubeck, Luc Devroye, Gábor Lugosi, Roberto Imbuzeiro Oliveira
2015	—	`conf`	Finite-Time Analysis of Projected Langevin Monte Carlo. NIPS Sébastien Bubeck, Ronen Eldan, Joseph Lehec
2015	J	`jnl`	Multi-scale exploration of convex functions and bandit convex optimization. CoRR Sébastien Bubeck, Ronen Eldan
2015	J	`jnl`	On the Influence of the Seed Graph in the Preferential Attachment Model. IEEE Trans. Netw. Sci. Eng. Sébastien Bubeck, Elchanan Mossel, Miklós Z. Rácz
2015	J	`jnl`	Sampling from a log-concave distribution with Projected Langevin Monte Carlo. CoRR Sébastien Bubeck, Ronen Eldan, Joseph Lehec
2015	A*	`conf`	The entropic barrier: a simple and optimal universal self-concordant barrier. COLT Sébastien Bubeck, Ronen Eldan
2014	J	`jnl`	Finding Adam in random growing trees. CoRR Sébastien Bubeck, Luc Devroye, Gábor Lugosi
2014	J	`jnl`	From trees to seeds: on the inference of the seed from large trees in the uniform attachment model. CoRR Sébastien Bubeck, Ronen Eldan, Elchanan Mossel, Miklós Z. Rácz
2014	A*	`conf`	Most Correlated Arms Identification. COLT Che-Yu Liu, Sébastien Bubeck
2014	J	`jnl`	Most Correlated Arms Identification. CoRR Che-Yu Liu, Sébastien Bubeck
2014	J	`jnl`	On the influence of the seed graph in the preferential attachment model. CoRR Sébastien Bubeck, Elchanan Mossel, Miklós Z. Rácz
2014	Misc	`conf`	Prior-free and prior-dependent regret bounds for Thompson Sampling. CISS Sébastien Bubeck, Che-Yu Liu
2014	J	`jnl`	Regret in Online Combinatorial Optimization. Math. Oper. Res. Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi
2014	J	`jnl`	Testing for high-dimensional geometry in random graphs. CoRR Sébastien Bubeck, Jian Ding, Ronen Eldan, Miklós Z. Rácz
2014	J	`jnl`	The entropic barrier: a simple and optimal universal self-concordant barrier. CoRR Sébastien Bubeck, Ronen Eldan
2014	J	`jnl`	Theory of Convex Optimization for Machine Learning. CoRR Sébastien Bubeck
2014	A*	`conf`	lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits. COLT Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck
2013	J	`jnl`	A note on the Bayesian regret of Thompson Sampling with an arbitrary prior CoRR Sébastien Bubeck, Che-Yu Liu
2013	J	`jnl`	Bandits With Heavy Tail. IEEE Trans. Inf. Theory Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
2013	J	`jnl`	Bounded regret in stochastic multi-armed bandits CoRR Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
2013	A*	`conf`	Bounded regret in stochastic multi-armed bandits. COLT Sébastien Bubeck, Vianney Perchet, Philippe Rigollet
2013	—	`conf`	Multiple Identifications in Multi-Armed Bandits. ICML (1) Sébastien Bubeck, Tengyao Wang, Nitin Viswanathan
2013	J	`jnl`	On Finding the Largest Mean Among Many. CoRR Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck
2013	J	`jnl`	Optimal discovery with probabilistic expert advice: finite time analysis and macroscopic optimality. J. Mach. Learn. Res. Sébastien Bubeck, Damien Ernst, Aurélien Garivier
2013	—	`conf`	Prior-free and prior-dependent regret bounds for Thompson Sampling. NIPS Sébastien Bubeck, Che-Yu Liu
2013	J	`jnl`	lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits. CoRR Kevin Jamieson, Matthew Malloy, Robert D. Nowak, Sébastien Bubeck
2012	J	`jnl`	Bandits with heavy tail CoRR Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
2012	J	`jnl`	Multiple Identifications in Multi-Armed Bandits CoRR Sébastien Bubeck, Tengyao Wang, Nitin Viswanathan
2012	—	`conf`	Optimal discovery with probabilistic expert advice. CDC Sébastien Bubeck, Damien Ernst, Aurélien Garivier
2012	J	`jnl`	Optimal discovery with probabilistic expert advice: finite time analysis and macroscopic optimality CoRR Sébastien Bubeck, Damien Ernst, Aurélien Garivier
2012	J	`jnl`	Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems CoRR Sébastien Bubeck, Nicolò Cesa-Bianchi
2012	J	`jnl`	Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems. Found. Trends Mach. Learn. Sébastien Bubeck, Nicolò Cesa-Bianchi
2012	J	`jnl`	Regret in Online Combinatorial Optimization CoRR Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi
2012	A*	`conf`	The Best of Both Worlds: Stochastic and Adversarial Bandits. COLT Sébastien Bubeck, Aleksandrs Slivkins
2012	J	`jnl`	The best of both worlds: stochastic and adversarial bandits CoRR Sébastien Bubeck, Aleksandrs Slivkins
2012	A*	`conf`	Towards Minimax Policies for Online Linear Optimization with Bandit Feedback. COLT Sébastien Bubeck, Nicolò Cesa-Bianchi, Sham M. Kakade
2012	J	`jnl`	Towards minimax policies for online linear optimization with bandit feedback CoRR Sébastien Bubeck, Nicolò Cesa-Bianchi, Sham M. Kakade
2011	B	`conf`	Lipschitz Bandits without the Lipschitz Constant. ALT Sébastien Bubeck, Gilles Stoltz, Jia Yuan Yu
2011	A*	`conf`	Minimax Policies for Combinatorial Prediction Games. COLT Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi
2011	—	`conf`	Multi-Bandit Best Arm Identification. NIPS Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric, Sébastien Bubeck
2011	J	`jnl`	Optimal discovery with probabilistic expert advice CoRR Sébastien Bubeck, Damien Ernst, Aurélien Garivier
2011	J	`jnl`	Pure exploration in finitely-armed and continuous-armed bandits. Theor. Comput. Sci. Sébastien Bubeck, Rémi Munos, Gilles Stoltz
2010	A*	`conf`	Best Arm Identification in Multi-Armed Bandits. COLT Jean-Yves Audibert, Sébastien Bubeck, Rémi Munos
2010	A*	`conf`	Open Loop Optimistic Planning. COLT Sébastien Bubeck, Rémi Munos
2010	J	`jnl`	Regret Bounds and Minimax Policies under Partial Monitoring. J. Mach. Learn. Res. Jean-Yves Audibert, Sébastien Bubeck
2010	J	`jnl`	X-Armed Bandits CoRR Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári
2009	A*	`conf`	Minimax Policies for Adversarial and Stochastic Bandits. COLT Jean-Yves Audibert, Sébastien Bubeck
2009	J	`jnl`	Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions. J. Mach. Learn. Res. Sébastien Bubeck, Ulrike von Luxburg
2009	B	`conf`	Pure Exploration in Multi-armed Bandits Problems. ALT Sébastien Bubeck, Rémi Munos, Gilles Stoltz
2008	—	`conf`	Online Optimization in X-Armed Bandits. NIPS Sébastien Bubeck, Rémi Munos, Gilles Stoltz, Csaba Szepesvári
2008	J	`jnl`	Pure Exploration for Multi-Armed Bandit Problems CoRR Sébastien Bubeck, Rémi Munos, Gilles Stoltz
2007	—	`conf`	Consistent Minimization of Clustering Objective Functions. NIPS Ulrike von Luxburg, Sébastien Bubeck, Stefanie Jegelka, Michael Kaufmann