| Stochastic simultaneous optimistic optimization M Valko, A Carpentier, R Munos International Conference on Machine Learning, 19-27, 2013 | 92 | 2013 |
| Bandit theory meets compressed sensing for high dimensional stochastic linear bandit A Carpentier, R Munos Artificial Intelligence and Statistics, 190-198, 2012 | 79 | 2012 |
| An optimal algorithm for the thresholding bandit problem A Locatelli, M Gutzeit, A Carpentier International Conference on Machine Learning, 1690-1698, 2016 | 77 | 2016 |
| Upper-confidence-bound algorithms for active learning in multi-armed bandits A Carpentier, A Lazaric, M Ghavamzadeh, R Munos, P Auer International Conference on Algorithmic Learning Theory, 189-203, 2011 | 66 | 2011 |
| Tight (lower) bounds for the fixed budget best arm identification bandit problem A Carpentier, A Locatelli Conference on Learning Theory, 590-604, 2016 | 53 | 2016 |
| Simple regret for infinitely many armed bandits A Carpentier, M Valko International Conference on Machine Learning, 1133-1141, 2015 | 53 | 2015 |
| Revealing graph bandits for maximizing local influence A Carpentier, M Valko Artificial Intelligence and Statistics, 10-18, 2016 | 36 | 2016 |
| Extreme bandits A Carpentier, M Valko Neural Information Processing Systems, 2014 | 33 | 2014 |
| Finite-time analysis of stratified sampling for monte carlo A Carpentier, R Munos NIPS-Twenty-Fifth Annual Conference on Neural Information Processing Systems, 2011 | 31 | 2011 |
| Adaptivity to smoothness in x-armed bandits A Locatelli, A Carpentier Conference on Learning Theory, 1463-1492, 2018 | 30 | 2018 |
| Hybrid collaborative filtering with autoencoders F Strub, J Mary, R Gaudel arXiv preprint arXiv:1603.00806, 2016 | 27 | 2016 |
| Two-sample tests for large random graphs using network statistics D Ghoshdastidar, M Gutzeit, A Carpentier, U von Luxburg Conference on Learning Theory, 954-977, 2017 | 26 | 2017 |
| Uncertainty quantification for matrix compressed sensing and quantum tomography problems A Carpentier, J Eisert, D Gross, R Nickl High Dimensional Probability VIII, 385-430, 2019 | 23 | 2019 |
| Adaptive confidence sets for matrix completion A Carpentier, O Klopp, M Löffler, R Nickl Bernoulli 24 (4A), 2429-2460, 2018 | 20 | 2018 |
| Automatic motor task selection via a bandit algorithm for a brain-controlled button J Fruitet, A Carpentier, R Munos, M Clerc Journal of neural engineering 10 (1), 016012, 2013 | 20 | 2013 |
| Two-sample hypothesis testing for inhomogeneous random graphs D Ghoshdastidar, M Gutzeit, A Carpentier, U Von Luxburg Annals of Statistics 48 (4), 2208-2229, 2020 | 19 | 2020 |
| Adaptive and minimax optimal estimation of the tail coefficient A Carpentier, AKH Kim Statistica Sinica, 1133-1144, 2015 | 18 | 2015 |
| Adaptive estimation of the sparsity in the Gaussian vector model A Carpentier, N Verzelen Annals of Statistics 47 (1), 93-126, 2019 | 17 | 2019 |
| Honest and adaptive confidence sets in A Carpentier Electronic Journal of Statistics 7, 2875-2923, 2013 | 16 | 2013 |
| Rotting bandits are no harder than stochastic ones J Seznec, A Locatelli, A Carpentier, A Lazaric, M Valko The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 13 | 2019 |
