| Non-asymptotic pure exploration by solving games R Degenne, WM Koolen, P Ménard Advances in Neural Information Processing Systems 32, 2019 | 95 | 2019 |
| Gamification of pure exploration for linear bandits R Degenne, P Ménard, X Shang, M Valko International Conference on Machine Learning, 2432-2442, 2020 | 93 | 2020 |
| Pure exploration with multiple correct answers R Degenne, WM Koolen Advances in Neural Information Processing Systems 32, 2019 | 76 | 2019 |
| Anytime optimal algorithms in stochastic multi-armed bandits R Degenne, V Perchet International Conference on Machine Learning, 1587-1595, 2016 | 66 | 2016 |
| Combinatorial semi-bandit with known covariance R Degenne, V Perchet Advances in Neural Information Processing Systems 29, 2016 | 54 | 2016 |
| Top two algorithms revisited M Jourdan, R Degenne, D Baudry, R de Heide, E Kaufmann Advances in Neural Information Processing Systems 35, 26791-26803, 2022 | 40 | 2022 |
| Structure adaptive algorithms for stochastic bandits R Degenne, H Shao, W Koolen International Conference on Machine Learning, 2443-2452, 2020 | 39 | 2020 |
| Bridging the gap between regret minimization and best arm identification, with application to a/b tests R Degenne, T Nedelec, C Calauzènes, V Perchet The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 22 | 2019 |
| On the existence of a complexity in fixed budget bandit identification R Degenne The Thirty Sixth Annual Conference on Learning Theory, 1131-1154, 2023 | 19 | 2023 |
| Dealing with unknown variances in best-arm identification M Jourdan, D Rémy, K Emilie International Conference on Algorithmic Learning Theory, 776-849, 2023 | 15 | 2023 |
| Dealing with misspecification in fixed-confidence linear top-m identification C Réda, A Tirinzoni, R Degenne Advances in Neural Information Processing Systems 34, 25489-25501, 2021 | 11 | 2021 |
| Bandits with side observations: Bounded vs. logarithmic regret R Degenne, E Garcelon, V Perchet arXiv preprint arXiv:1807.03558, 2018 | 11 | 2018 |
| On elimination strategies for bandit fixed-confidence identification A Tirinzoni, R Degenne Advances in Neural Information Processing Systems 35, 18586-18598, 2022 | 8 | 2022 |
| Non-asymptotic analysis of a ucb-based top two algorithm M Jourdan, R Degenne Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Accelerated gradient temporal difference learning algorithms D Meyer, R Degenne, A Omrane, H Shen 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014 | 7 | 2014 |
| An -Best-Arm Identification Algorithm for Fixed-Confidence and Beyond M Jourdan, R Degenne, E Kaufmann Advances in Neural Information Processing Systems 36, 16578-16649, 2023 | 6 | 2023 |
| Impact of structure on the design and analysis of bandit algorithms R Degenne Université Paris Cité, 2019 | 5 | 2019 |
| Online sign identification: Minimization of the number of errors in thresholding bandits R Ouhamma, OA Maillard, V Perchet Advances in Neural Information Processing Systems 34, 18577-18589, 2021 | 3 | 2021 |
| Choosing Answers in Epsilon-Best-Answer Identification for Linear Bandits M Jourdan, R Degenne International Conference on Machine Learning, 10384-10430, 2022 | 2 | 2022 |
| Fast asymptotically optimal algorithms for non-parametric stochastic bandits D Baudry, F Pesquerel, R Degenne, OA Maillard Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
Vianney PerchetCrest, ENSAE & Criteo AI LabVerified email at normalesup.org
