Sébastien Bubeck

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 111

Top Venues

Publications

Marah I Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat S. Behl, Alon Benhaim, Misha Bilenko, Johan Bjorck, Sébastien Bubeck, Martin Cai, Caio César Teodoro Mendes, Weizhu Chen, Vishrav Chaudhary, Parul Chopra, Allie Del Giorno, Gustavo de Rosa, Matthew Dixon, Ronen Eldan, Dan Iter, Amit Garg, Abhishek Goswami, Suriya Gunasekar, Emman Haider, Junheng Hao, Russell J. Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahoud Khademi, Lev Kurilenko, James R. Lee, Yin Tat Lee, Yuanzhi Li, Chen Liang, Weishung Liu, Eric Lin, Zeqi Lin, Piyush Madan, Arindam Mitra, Hardik Modi, Anh Nguyen, Brandon Norick, Barun Patra, Daniel Perez-Becker, Thomas Portet, Reid Pryzant, Heyang Qin, Marko Radmilac, Corby Rosset, Sambudha Roy, Olatunji Ruwase, Olli Saarikivi, Amin Saied, Adil Salim, Michael Santacroce, Shital Shah, Ning Shang, Hiteshi Sharma, Xia Song, Masahiro Tanaka, Xin Wang, Rachel Ward, Guanhua Wang, Philipp Witte, Michael Wyatt, Can Xu, Jiahang Xu, Sonali Yadav, Fan Yang, Ziyi Yang, Donghan Yu, Chengruidong Zhang, Cyril Zhang, Jianwen Zhang, Li Lyna Zhang, Yi Zhang, Yue Zhang, Yunan Zhang, Xiren Zhou
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone. CoRR (2024)
Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
How to Fine-Tune Vision Models with SGD. ICLR (2024)
Beibin Li, Yi Zhang, Sébastien Bubeck, Jeevan Pathuri, Ishai Menache
Small Language Models for Application Interactions: A Case Study. CoRR (2024)
Sébastien Bubeck, Dan Mikulincer
How to Trap a Gradient Flow. SIAM J. Comput. 53 (4) (2024)
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
Textbooks Are All You Need. CoRR (2023)
Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, Allie Del Giorno, Suriya Gunasekar, Yin Tat Lee
Textbooks Are All You Need II: phi-1.5 technical report. CoRR (2023)
Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Yuanzhi Li, Yi Zhang
Positional Description Matters for Transformers Arithmetic. CoRR (2023)
Sébastien Bubeck, Christian Coester, Yuval Rabani
The Randomized k-Server Conjecture Is False! STOC (2023)
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
Sparks of Artificial General Intelligence: Early experiments with GPT-4. CoRR (2023)
Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
Competitively Chasing Convex Bodies. SIAM J. Comput. 52 (1) (2023)
Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation. ACL (Findings) (2023)
Sinho Chewi, Sébastien Bubeck, Adil Salim
On the complexity of finding stationary points of smooth functions in one dimension. ALT (2023)
Sébastien Bubeck, Mark Sellke
A Universal Law of Robustness via Isoperimetry. J. ACM 70 (2) (2023)
Sébastien Bubeck, Mark Sellke
First-Order Bayesian Regret Analysis of Thompson Sampling. IEEE Trans. Inf. Theory 69 (3) (2023)
Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang
TinyGSM: achieving >80% on GSM8k with small language models. CoRR (2023)
Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
Learning threshold neurons via edge of stability. NeurIPS (2023)
Mojan Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio Cesar Teodoro Mendes, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey
LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models. NeurIPS (2022)
Yi Zhang, Arturs Backurs, Sébastien Bubeck, Ronen Eldan, Suriya Gunasekar, Tal Wagner
Unveiling Transformers with LEGO: a synthetic reasoning task. CoRR (2022)
Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
Data Augmentation as Feature Manipulation. ICML (2022)
Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
Data Augmentation as Feature Manipulation: a story of desert cows and grass cows. CoRR (2022)
Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao
AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers. CoRR (2022)
Sébastien Bubeck, Christian Coester, Yuval Rabani
Shortest Paths without a Map, but with an Entropic Regularizer. CoRR (2022)
Sébastien Bubeck, Christian Coester, Yuval Rabani
Shortest Paths without a Map, but with an Entropic Regularizer. FOCS (2022)
Mojan Javaheripi, Shital Shah, Subhabrata Mukherjee, Tomasz L. Religa, Caio C. T. Mendes, Gustavo H. de Rosa, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey
LiteTransformerSearch: Training-free On-device Search for Efficient Autoregressive Language Models. CoRR (2022)
Sébastien Bubeck, Christian Coester, Yuval Rabani
The Randomized k-Server Conjecture is False! CoRR (2022)
Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
Learning threshold neurons via the "edge of stability". CoRR (2022)
Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
How to Fine-Tune Vision Models with SGD. CoRR (2022)
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
A single gradient step finds adversarial examples on random two-layers neural networks. NeurIPS (2021)
Sébastien Bubeck, Yuval Rabani, Mark Sellke
Online Multiserver Convex Chasing and Optimization. SODA (2021)
Debadeepta Dey, Shital Shah, Sébastien Bubeck
FEAR: A Simple Lightweight Method to Rank Architectures. CoRR (2021)
Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri
Adversarial Examples in Multi-Layer Random ReLU Networks. NeurIPS (2021)
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Rémi Tachet des Combes
A single gradient step finds adversarial examples on random two-layers neural networks. CoRR (2021)
Sébastien Bubeck, Ronen Eldan, Yin Tat Lee
Kernel-based Methods for Bandit Convex Optimization. J. ACM 68 (4) (2021)
Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri
Adversarial Examples in Multi-Layer Random ReLU Networks. CoRR (2021)
Sébastien Bubeck, Yuanzhi Li, Dheeraj M. Nagaraj
A Law of Robustness for Two-Layers Neural Networks. COLT (2021)
Sébastien Bubeck, Thomas Budzinski, Mark Sellke
Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. COLT (2021)
Sébastien Bubeck, Mark Sellke
A Universal Law of Robustness via Isoperimetry. NeurIPS (2021)
Sébastien Bubeck, Niv Buchbinder, Christian Coester, Mark Sellke
Metrical Service Systems with Transformations. ITCS (2021)
Sébastien Bubeck, Mark Sellke
A Universal Law of Robustness via Isoperimetry. CoRR (2021)
Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee
Metrical Task Systems on Trees via Mirror Descent and Unfair Gluing. SIAM J. Comput. 50 (3) (2021)
Sébastien Bubeck, Mark Sellke
First-Order Bayesian Regret Analysis of Thompson Sampling. ALT (2020)
Sébastien Bubeck, Niv Buchbinder, Christian Coester, Mark Sellke
Metrical Service Systems with Transformations. CoRR (2020)
Hadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. ICML (2020)
Hadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. CoRR (2020)
Sébastien Bubeck, Sitan Chen, Jerry Li
Entanglement is Necessary for Optimal Quantum Property Testing. FOCS (2020)
Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
Network size and weights size for memorization with two-layers neural networks. CoRR (2020)
Sébastien Bubeck, Thomas Budzinski
Coordination without communication: optimal regret in two players multi-armed bandits. COLT (2020)
Sébastien Bubeck, Yuanzhi Li, Dheeraj Nagaraj
A law of robustness for two-layers neural networks. CoRR (2020)
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
Online Learning for Active Cache Synchronization. CoRR (2020)
Sébastien Bubeck, Dan Mikulincer
How to Trap a Gradient Flow. COLT (2020)
Sébastien Bubeck, Yuval Rabani, Mark Sellke
Online Multiserver Convex Chasing and Optimization. CoRR (2020)
Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
Network size and size of the weights in memorization with two-layers neural networks. NeurIPS (2020)
Sébastien Bubeck, Yuval Rabani
Parametrized Metrical Task Systems. APPROX-RANDOM (2020)
Sébastien Bubeck, Thomas Budzinski
Coordination without communication: optimal regret in two players multi-armed bandits. CoRR (2020)
Sébastien Bubeck, Bo'az Klartag, Yin Tat Lee, Yuanzhi Li, Mark Sellke
Chasing Nested Convex Bodies Nearly Optimally. SODA (2020)
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
Online Learning for Active Cache Synchronization. ICML (2020)
Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke
Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. COLT (2020)
Sébastien Bubeck, Sitan Chen, Jerry Li
Entanglement is Necessary for Optimal Quantum Property Testing. CoRR (2020)
Sébastien Bubeck, Thomas Budzinski, Mark Sellke
Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions. CoRR (2020)
Sébastien Bubeck, Dan Mikulincer
How to trap a gradient flow. CoRR (2020)
Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang, Rad Niazadeh
Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing. J. Mach. Learn. Res. 20 (2019)
Kevin Scaman, Francis R. Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié
Optimal Convergence Rates for Convex Distributed Optimization in Networks. J. Mach. Learn. Res. 20 (2019)
Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
Complexity of Highly Parallel Non-Smooth Convex Optimization. CoRR (2019)
Sébastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn
Adversarial examples from computational constraints. ICML (2019)
Sébastien Bubeck, Ronen Eldan
The Entropic Barrier: Exponential Families, Log-Concave Geometry, and Self-Concordance. Math. Oper. Res. 44 (1) (2019)
Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
Competitively chasing convex bodies. STOC (2019)
Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. NeurIPS (2019)
Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee
Metrical task systems on trees via mirror descent and unfair gluing. SODA (2019)
Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei
Improved Path-length Regret Bounds for Bandits. CoRR (2019)
Alexander V. Gasnikov, Pavel E. Dvurechensky, Eduard A. 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
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives. COLT (2019)
Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya P. Razenshteyn, Sébastien Bubeck
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. CoRR (2019)
Sébastien Bubeck, Yuval Rabani
Parametrized Metrical Task Systems. CoRR (2019)
Sébastien Bubeck, Yuanzhi Li, Haipeng Luo, Chen-Yu Wei
Improved Path-length Regret Bounds for Bandits. COLT (2019)
Sébastien Bubeck, Mark Sellke
First-Order Regret Analysis of Thompson Sampling. CoRR (2019)
Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
Near-optimal method for highly smooth convex optimization. COLT (2019)
Sébastien Bubeck, Yuanzhi Li, Yuval Peres, Mark Sellke
Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without. CoRR (2019)
C. J. Argue, Sébastien Bubeck, Michael B. Cohen, Anupam Gupta, Yin Tat Lee
A Nearly-Linear Bound for Chasing Nested Convex Bodies. SODA (2019)
Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
Complexity of Highly Parallel Non-Smooth Convex Optimization. NeurIPS (2019)
Zeyuan Allen-Zhu, Sébastien Bubeck, Yuanzhi Li
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits. CoRR (2018)
Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
Chasing Nested Convex Bodies Nearly Optimally. CoRR (2018)
C. J. Argue, Sébastien Bubeck, Michael B. Cohen, Anupam Gupta, Yin Tat Lee
A Nearly-Linear Bound for Chasing Nested Convex Bodies. CoRR (2018)
Sébastien Bubeck, Ronen Eldan, Joseph Lehec
Sampling from a Log-Concave Distribution with Projected Langevin Monte Carlo. Discret. Comput. Geom. 59 (4) (2018)
Chi Jin, Zeyuan Allen-Zhu, Sébastien Bubeck, Michael I. Jordan
Is Q-learning Provably Efficient? CoRR (2018)
Sébastien Bubeck, Yin Tat Lee, Eric Price, Ilya P. Razenshteyn
Adversarial Examples from Cryptographic Pseudo-Random Generators. CoRR (2018)
Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee
Metrical task systems on trees via mirror descent and unfair gluing. CoRR (2018)
Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, Yuanzhi Li
regression provably beyond self-concordance and in input-sparsity time. STOC (2018)
Sébastien Bubeck, Philippe Rigollet
Conference on Learning Theory 2018: Preface. COLT (2018)
Zeyuan Allen-Zhu, Sébastien Bubeck, Yuanzhi Li
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits. ICML (2018)
Chi Jin, Zeyuan Allen-Zhu, Sébastien Bubeck, Michael I. Jordan
Is Q-Learning Provably Efficient? NeurIPS (2018)
Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, James R. Lee, Aleksander Madry
k-server via multiscale entropic regularization. STOC (2018)
Kevin Scaman, Francis R. Bach, Sébastien Bubeck, Laurent Massoulié, Yin Tat Lee
Optimal Algorithms for Non-Smooth Distributed Optimization in Networks. NeurIPS (2018)
Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Mark Sellke
Competitively Chasing Convex Bodies. CoRR (2018)
Sébastien Bubeck, Eric Price, Ilya P. Razenshteyn
Adversarial examples from computational constraints. CoRR (2018)
Sébastien Bubeck, Michael B. Cohen, Yuanzhi Li
Sparsity, variance and curvature in multi-armed bandits. ALT (2018)
Sébastien Bubeck, Michael B. Cohen, James R. Lee, Yin Tat Lee, Aleksander Madry
k-server via multiscale entropic regularization. CoRR (2017)
Omer Angel, Sébastien Bubeck, Yuval Peres, Fan Wei
Local max-cut in smoothed polynomial time. STOC (2017)
Sébastien Bubeck, Michael B. Cohen, Yin Tat Lee, Yuanzhi Li
regression provably beyond self-concordance and in input-sparsity time. CoRR (2017)
Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang, Rad Niazadeh
Online Auctions and Multi-scale Online Learning. EC (2017)
Sébastien Bubeck, Yin Tat Lee, Ronen Eldan
Kernel-based methods for bandit convex optimization. STOC (2017)
Sébastien Bubeck, Luc Devroye, Gábor Lugosi
Finding Adam in random growing trees. Random Struct. Algorithms 50 (2) (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sébastien Bubeck