Sébastien Bubeck

39 papers receiving 3.1k citations

Hit Papers

Benefits, Limits,...2012202620162021202320122012250500750

Peers

Sébastien Bubeck
Comparison fields: 5 of 151
  • Artificial Intelligence 1.6k
  • Management Science and Operations Research 1.5k
  • Computer Networks and Communications 744
  • Health Informatics 684
  • Electrical and Electronic Engineering 431
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Citations per field
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Citations per year

Countries citing papers authored by Sébastien Bubeck

Since Specialization
Citations

This map shows the geographic impact of Sébastien Bubeck's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sébastien Bubeck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sébastien Bubeck more than expected).

Fields of papers citing papers by Sébastien Bubeck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sébastien Bubeck. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sébastien Bubeck. The network helps show where Sébastien Bubeck may publish in the future.

Co-authorship network of co-authors of Sébastien Bubeck

This figure shows the co-authorship network connecting the top 25 collaborators of Sébastien Bubeck. A scholar is included among the top collaborators of Sébastien Bubeck based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sébastien Bubeck. Sébastien Bubeck is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1
Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicinebreakdown →
894
2
Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives
7
3
Near-optimal method for highly smooth convex optimization
6
4
Complexity of Highly Parallel Non-Smooth Convex Optimization
1
5
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
29
6
Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing
6
7
Adversarial examples from computational constraints
8
8 3
9
Is Q-learning Provably Efficient?
114
10
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits.
0
11
Finite-time analysis of projected Langevin Monte Carlo
5
12
lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits
40
13
Most Correlated Arms Identification
1
14
Bounded regret in stochastic multi-armed bandits
18
15
X -Armed Bandits
95
16
Minimax Policies for Combinatorial Prediction Games
1
17 87
18 34
19
Online Optimization in X-Armed Bandits
68
20
Consistent Minimization of Clustering Objective Functions
8

About Sébastien Bubeck

Sébastien Bubeck is a scholar working on Management Science and Operations Research, Artificial Intelligence and Numerical Analysis, having authored 41 papers that have together received 3.2k indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (19 papers), Optimization and Search Problems (14 papers) and Machine Learning and Algorithms (12 papers). The work is most often cited by research in Health Informatics (684 citations), Management Science and Operations Research (1.5k citations) and Artificial Intelligence (1.6k citations). Sébastien Bubeck has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Joseph Petro, Gilles Stoltz, Rémi Munos, Gábor Lugosi, Csaba Szepesvári, Zeyuan Allen-Zhu, Michael I. Jordan, Chi Jin, Ulrike von Luxburg and Nicolò Cesa‐Bianchi. Their work appears in journals such as New England Journal of Medicine, IEEE Transactions on Information Theory and Journal of Machine Learning Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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