I am a PhD student in Machine Learning at CNRS in the Inria ScooL team (formerly SequeL), under the direction of Emilie Kaufmann and Odalric-Ambrym Maillard. I explore alternative approaches to the classical UCB/Thompson Sampling in the Multi-Armed Bandits problem, with algorithms based on sub-sampling or re-sampling of collected data. By using a few information on the arm’s distribution, this approach allows to design algorithms that can achieve good theoretical guarantees in diverse settings such as the classical K-armed bandit problems, bandits in non-stationary environments, or risk-aware bandits. My research interests also include reinforcement learning, statistics, and machine learning in general.
PhD Student, 2019-now
CNRS/Inria Lille, SequeL/ScooL team
MSc Mathématiques Vision Apprentissage (MVA), 2019
MSc in Statistics and Computer Science, 2019