Weighted linear bandits for non-stationary environments Y Russac, C Vernade, O Cappé NeurIPS 2019, 2019 | 125 | 2019 |
Algorithms for non-stationary generalized linear bandits Y Russac, O Cappé, A Garivier arXiv preprint arXiv:2003.10113, 2020 | 24 | 2020 |
Embeddings of categorical variables for sequential data in fraud context Y Russac, O Caelen, L He-Guelton AMLTA 2018, 2018 | 22 | 2018 |
A/B/n Testing with Control in the Presence of Subpopulations Y Russac, C Katsimerou, D Bohle, O Cappé, A Garivier, W Koolen NeurIPS 2021, 2021 | 20 | 2021 |
Self-Concordant Analysis of Generalized Linear Bandits with Forgetting Y Russac, L Faury, O Cappé, A Garivier AISTATS 2021, 2021 | 13 | 2021 |
On Limited-Memory Subsampling Strategies for Bandits D Baudry, Y Russac, O Cappé ICML 2021, 2021 | 12 | 2021 |
Regret bounds for generalized linear bandits under parameter drift L Faury, Y Russac, M Abeille, C Calauzènes arXiv preprint arXiv:2103.05750, 2021 | 11 | 2021 |
Efficient Algorithms for Extreme Bandits D Baudry, Y Russac, E Kaufmann AISTATS 2022, 2022 | 6 | 2022 |
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 |
Sequential decision problems in non-stationary environments Y Russac Université Paris sciences et lettres, 2022 | | 2022 |