Scholar
Odalric-Ambrym Maillard
Google Scholar ID: 7EweMdoAAAAJ
Inria Lille - Nord Europe
Multi-armed Bandits
Stochastic Dynamical Systems
Statistical Learning
Reinforcement Learning
Random matrices
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
2,204
H-index
25
i10-index
54
Publications
20
Co-authors
11
list available
Publications
13 items
Information-Based Exploration via Random Features for Reinforcement Learning
2026
Cited
0
Bandits for Efficient Experimentation: Adapting to Control Group, Preferences, and Context Drifts
2026
Cited
0
Pliable rejection sampling
2026
Cited
0
How Hard is it to Confuse a World Model?
2025
Cited
0
The Confusing Instance Principle for Online Linear Quadratic Control
2025
Cited
0
Asymptotically Optimal Problem-Dependent Bandit Policies for Transfer Learning
2025
Cited
0
Offline Goal-Conditioned Reinforcement Learning with Projective Quasimetric Planning
2025
Cited
0
A Continual Offline Reinforcement Learning Benchmark for Navigation Tasks
2025
Cited
0
Load more
Co-authors
6 total
Rémi Munos
FAIR, Meta
Philippe Preux
Professor of computer science, Université de Lille, LIFL, SequeL, INRIA
Shie Mannor
Professor of Electrical Engineering @ Technion & Researcher @ Nvidia
Olivier Cappé
CNRS
Alessandro Lazaric
Research Scientist, Facebook Artificial Intelligence Research
Rémi Bardenet
CNRS, CRIStAL, Ecole Centrale Lille, Univ. Lille, France
