Publications

Dorian Baudry, Nadav Merlis, Mathieu Molina, Hugo Richard, Vianney Perchet (2024). Multi-Armed Bandits with Guaranteed Revenue per Arm. AISTATS 2024.

Romain Gautron, Dorian Baudry, Myriam Adam, Gatien N. Falconnier, Gerrit Hoogenboom, Brian King, Marc Corbeels (2024). A new adaptive identification strategy of best crop management with farmers. [Field Crops Research].

Dorian Baudry, Kazuya Suzuki, Junya Honda (2023). A General Recipe for the Analysis of Randomized Multi-Armed Bandit Algorithms. [Preprint].

Dorian Baudry, Fabien Pesquerel, Rémy Degenne, Odalric-Ambrym Maillard (2023). Fast asymptotically optimal algorithms for non-parametric stochastic bandits. NeurIPS 2023.

Dorian Baudry (2022). Non-parametric algorithms for Multi-Armed Bandits. [PhD Thesis].

Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne De Heide, Emilie Kaufmann (2022). Top Two Algorithms Revisited. NeurIPS 2022.

Dorian Baudry, Yoan Russac, Emilie Kaufmann (2022). Efficient Algorithms for Extreme Bandits. AISTATS 2022.

Dorian Baudry, Patrick Saux, Odalric-Ambrym Maillard (2021). From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits. NeurIPS 2021.

Dorian Baudry, Yoan Russac, Olivier Cappé (2021). On Limited-Memory Subsampling Strategies for Bandits. ICML 2021.

Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard (2021). Optimal Thompson Sampling strategies for support-aware CVaR bandits. ICML 2021.

Preprint PDF Code

Dorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard (2020). Sub-Sampling Algorithms for Efficient Non-Parametric Bandit Exploration. NeurIPS 2020.