Linear thompson sampling revisited M Abeille, A Lazaric Artificial Intelligence and Statistics, 176-184, 2017 | 277 | 2017 |
Improved regret bounds for thompson sampling in linear quadratic control problems M Abeille, A Lazaric International Conference on Machine Learning, 1-9, 2018 | 108 | 2018 |
Improved optimistic algorithms for logistic bandits L Faury, M Abeille, C Calauzènes, O Fercoq International Conference on Machine Learning, 3052-3060, 2020 | 86 | 2020 |
Thompson sampling for linear-quadratic control problems M Abeille, A Lazaric Artificial intelligence and statistics, 1246-1254, 2017 | 72 | 2017 |
Efficient optimistic exploration in linear-quadratic regulators via lagrangian relaxation M Abeille, A Lazaric International Conference on Machine Learning, 23-31, 2020 | 40 | 2020 |
Instance-wise minimax-optimal algorithms for logistic bandits M Abeille, L Faury, C Calauzènes International Conference on Artificial Intelligence and Statistics, 3691-3699, 2021 | 38 | 2021 |
Thompson sampling in non-episodic restless bandits YH Jung, M Abeille, A Tewari arXiv preprint arXiv:1910.05654, 2019 | 24 | 2019 |
Jointly efficient and optimal algorithms for logistic bandits L Faury, M Abeille, KS Jun, C Calauzènes International Conference on Artificial Intelligence and Statistics, 546-580, 2022 | 20 | 2022 |
LQG for portfolio optimization M Abeille, A Lazaric, X Brokmann arXiv preprint arXiv:1611.00997, 2016 | 18 | 2016 |
Regret bounds for generalized linear bandits under parameter drift L Faury, Y Russac, M Abeille, C Calauzènes arXiv preprint arXiv:2103.05750, 2021 | 13 | 2021 |
Explicit shading strategies for repeated truthful auctions M Abeille, C Calauzènes, NE Karoui, T Nedelec, V Perchet arXiv preprint arXiv:1805.00256, 2018 | 9 | 2018 |
Real-time optimisation for online learning in auctions L Croissant, M Abeille, C Calauzènes International Conference on Machine Learning, 2217-2226, 2020 | 8 | 2020 |
Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems T Nedelec, M Abeille, C Calauzènes, N El Karoui, B Heymann, V Perchet arXiv preprint arXiv:1808.06979, 2018 | 6 | 2018 |
Diffusive limit approximation of pure-jump optimal stochastic control problems M Abeille, B Bouchard, L Croissant Journal of Optimization Theory and Applications 196 (1), 147-176, 2023 | 5 | 2023 |
A technical note on non-stationary parametric bandits: Existing mistakes and preliminary solutions L Faury, Y Russac, M Abeille, C Calauzènes Algorithmic Learning Theory, 619-626, 2021 | 4 | 2021 |
Exploration-Exploitation with Thompson Sampling in Linear Systems M Abeille Université de Lille 1, 2017 | 2 | 2017 |
Thresholding at the monopoly price: an agnostic way to improve bidding strategies in revenue-maximizing auctions T Nedelec, M Abeille, C Calauzènes, B Heymann, V Perchet, NE Karoui arXiv preprint arXiv:1808.06979, 2018 | 1 | 2018 |
Near-continuous time Reinforcement Learning for continuous state-action spaces L Croissant, M Abeille, B Bouchard International Conference on Algorithmic Learning Theory, 444-498, 2024 | | 2024 |
Diffusive limit approximation of pure jump optimal ergodic control problems M Abeille, B Bouchard, L Croissant | | 2022 |
Optimal Regret Bounds for Generalized Linear Bandits under Parameter Drift L Faury, Y Russac, M Abeille, C Calauzènes Proceedings of Machine Learning Research vol 132, 1-37, 2021 | | 2021 |