| Pure exploration in multi-armed bandits problems S Bubeck, R Munos, G Stoltz Algorithmic Learning Theory: 20th International Conference, ALT 2009, Porto …, 2009 | 633 | 2009 |
| X-Armed Bandits. S Bubeck, R Munos, G Stoltz, C Szepesvári Journal of Machine Learning Research 12 (5), 2011 | 515 | 2011 |
| Kullback-Leibler upper confidence bounds for optimal sequential allocation O Cappé, A Garivier, OA Maillard, R Munos, G Stoltz The Annals of Statistics, 1516-1541, 2013 | 438 | 2013 |
| Pure exploration in finitely-armed and continuous-armed bandits S Bubeck, R Munos, G Stoltz Theoretical Computer Science 412 (19), 1832-1852, 2011 | 325 | 2011 |
| Online optimization in X-armed bandits S Bubeck, G Stoltz, C Szepesvári, R Munos Advances in Neural Information Processing Systems 21, 2008 | 276 | 2008 |
| Improved second-order bounds for prediction with expert advice N Cesa-Bianchi, Y Mansour, G Stoltz Machine Learning 66, 321-352, 2007 | 253 | 2007 |
| Explore first, exploit next: The true shape of regret in bandit problems A Garivier, P Ménard, G Stoltz Mathematics of Operations Research 44 (2), 377-399, 2019 | 206 | 2019 |
| A second-order bound with excess losses P Gaillard, G Stoltz, T Van Erven Conference on Learning Theory, 176-196, 2014 | 178 | 2014 |
| A finite-time analysis of multi-armed bandits problems with kullback-leibler divergences OA Maillard, R Munos, G Stoltz Proceedings of the 24th annual Conference On Learning Theory, 497-514, 2011 | 167 | 2011 |
| Regret minimization under partial monitoring N Cesa-Bianchi, G Lugosi, G Stoltz Mathematics of Operations Research 31 (3), 562-580, 2006 | 144 | 2006 |
| Minimizing regret with label efficient prediction N Cesa-Bianchi, G Lugosi, G Stoltz IEEE Transactions on Information Theory 51 (6), 2152-2162, 2005 | 130 | 2005 |
| Forecasting electricity consumption by aggregating specialized experts: A review of the sequential aggregation of specialized experts, with an application to Slovakian and … M Devaine, P Gaillard, Y Goude, G Stoltz Machine Learning 90, 231-260, 2013 | 129 | 2013 |
| Learning correlated equilibria in games with compact sets of strategies G Stoltz, G Lugosi Games and Economic Behavior 59 (1), 187-208, 2007 | 122 | 2007 |
| Do countries falsify economic data strategically? Some evidence that they might T Michalski, G Stoltz Review of Economics and Statistics 95 (2), 591-616, 2013 | 119 | 2013 |
| Internal regret in on-line portfolio selection G Stoltz, G Lugosi Machine Learning 59, 125-159, 2005 | 117 | 2005 |
| Mirror descent meets fixed share (and feels no regret) N Cesa-Bianchi, P Gaillard, G Lugosi, G Stoltz Advances in Neural Information Processing Systems 25, 2012 | 102 | 2012 |
| Ozone ensemble forecast with machine learning algorithms V Mallet, G Stoltz, B Mauricette Journal of Geophysical Research: Atmospheres 114 (D5), 2009 | 97 | 2009 |
| Lipschitz bandits without the lipschitz constant S Bubeck, G Stoltz, JY Yu Algorithmic Learning Theory: 22nd International Conference, ALT 2011, Espoo …, 2011 | 92 | 2011 |
| Fundamentals and exchange rate forecastability with simple machine learning methods C Amat, T Michalski, G Stoltz Journal of International Money and Finance 88, 1-24, 2018 | 82 | 2018 |
| Incomplete information and internal regret in prediction of individual sequences G Stoltz Université Paris Sud-Paris XI, 2005 | 65 | 2005 |
