| Weighted linear bandits for non-stationary environments Y Russac, C Vernade, O Cappé Advances in Neural Information Processing Systems 32, 2019 | 100 | 2019 |
| Multiple-play bandits in the position-based model P Lagrée, C Vernade, O Cappe Advances in Neural Information Processing Systems 29, 2016 | 92 | 2016 |
| Stochastic bandit models for delayed conversions C Vernade, O Cappé, V Perchet arXiv preprint arXiv:1706.09186, 2017 | 85 | 2017 |
| Stochastic rank-1 bandits S Katariya, B Kveton, C Szepesvari, C Vernade, Z Wen Artificial Intelligence and Statistics, 392-401, 2017 | 73 | 2017 |
| Linear bandits with stochastic delayed feedback C Vernade, A Carpentier, T Lattimore, G Zappella, B Ermis, M Brueckner International Conference on Machine Learning, 9712-9721, 2020 | 67* | 2020 |
| Eigengame: PCA as a nash equilibrium I Gemp, B McWilliams, C Vernade, T Graepel arXiv preprint arXiv:2010.00554, 2020 | 42 | 2020 |
| Bernoulli Rank-1 Bandits for Click Feedback C Szepesvari, B Kveton, S Katariya, C Vernade IJCAI, 2017 | 42* | 2017 |
| Confident off-policy evaluation and selection through self-normalized importance weighting I Kuzborskij, C Vernade, A Gyorgy, C Szepesvári International Conference on Artificial Intelligence and Statistics, 640-648, 2021 | 39 | 2021 |
| Stochastic bandits with arm-dependent delays AG Manegueu, C Vernade, A Carpentier, M Valko International Conference on Machine Learning, 3348-3356, 2020 | 39* | 2020 |
| Asymptotically optimal information-directed sampling J Kirschner, T Lattimore, C Vernade, C Szepesvári Conference on Learning Theory, 2777-2821, 2021 | 30 | 2021 |
| Solving bernoulli rank-one bandits with unimodal thompson sampling C Trinh, E Kaufmann, C Vernade, R Combes Algorithmic Learning Theory, 862-889, 2020 | 27 | 2020 |
| The elliptical potential lemma revisited A Carpentier, C Vernade, Y Abbasi-Yadkori arXiv preprint arXiv:2010.10182, 2020 | 18 | 2020 |
| Non-stationary delayed bandits with intermediate observations C Vernade, A Gyorgy, T Mann International Conference on Machine Learning, 9722-9732, 2020 | 16 | 2020 |
| Sparse stochastic bandits J Kwon, V Perchet, C Vernade arXiv preprint arXiv:1706.01383, 2017 | 15 | 2017 |
| Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond M Achab, S Clémençon, A Garivier, A Sabourin, C Vernade Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 13 | 2017 |
| Eigengame unloaded: When playing games is better than optimizing I Gemp, B McWilliams, C Vernade, T Graepel arXiv preprint arXiv:2102.04152, 2021 | 9 | 2021 |
| Non-stationary bandits and meta-learning with a small set of optimal arms MJ Azizi, T Duong, Y Abbasi-Yadkori, A György, C Vernade, ... arXiv preprint arXiv:2202.13001, 2022 | 3 | 2022 |
| Learning from missing data using selection bias in movie recommendation C Vernade, O Cappé 2015 IEEE International Conference on Data Science and Advanced Analytics …, 2015 | 3 | 2015 |
| POMRL: No-Regret Learning-to-Plan with Increasing Horizons K Khetarpal, C Vernade, B O'Donoghue, S Singh, T Zahavy arXiv preprint arXiv:2212.14530, 2022 | 1 | 2022 |
| Beyond Average Return in Markov Decision Processes A Marthe, A Garivier, C Vernade arXiv preprint arXiv:2310.20266, 2023 | | 2023 |
Olivier CappéCNRSVerified email at cnrs.fr
