| A survey of cross-validation procedures for model selection S Arlot, A Celisse Statistics Surveys 4, 40-79, 2010 | 2495 | 2010 |
| Data-driven calibration of penalties for least-squares regression S Arlot, P Massart The Journal of Machine Learning Research 10, 245-279, 2009 | 175 | 2009 |
| Model selection by resampling penalization S Arlot Electronic Journal of Statistics 3, 557-624, 2009 | 80 | 2009 |
| Resampling and model selection S Arlot | 79* | 2007 |
| V-fold cross-validation improved: V-fold penalization S Arlot Arxiv preprint arXiv:0802.0566, 2008 | 76* | 2008 |
| Segmentation of the mean of heteroscedastic data via cross-validation S Arlot, A Celisse Arxiv preprint arXiv:0902.3977, 2009 | 59 | 2009 |
| Some non-asymptotic results on resampling in high dimension, II: Multiple tests E Roquain, S Arlot, G Blanchard The Annals of Statistics 38 (1), 83-99, 2010 | 57* | 2010 |
| Data-driven calibration of linear estimators with minimal penalties S Arlot, F Bach Arxiv preprint arXiv:0909.1884, 2009 | 56* | 2009 |
| Kernel change-point detection S Arlot, A Celisse, Z Harchaoui arXiv preprint arXiv:1202.3878 6, 2012 | 51* | 2012 |
| A note on lazy training in supervised differentiable programming L Chizat, F Bach arXiv preprint arXiv:1812.07956, 2018 | 48 | 2018 |
| Some nonasymptotic results on resampling in high dimension, I: Confidence regions S Arlot, G Blanchard, E Roquain The Annals of Statistics 38 (1), 51-82, 2010 | 48 | 2010 |
| Analysis of purely random forests bias S Arlot, R Genuer arXiv preprint arXiv:1407.3939, 2014 | 43 | 2014 |
| Large-margin metric learning for constrained partitioning problems R Lajugie, F Bach, S Arlot International Conference on Machine Learning, 297-305, 2014 | 41 | 2014 |
| Choice of V for V-fold cross-validation in least-squares density estimation S Arlot, M Lerasle The Journal of Machine Learning Research 17 (1), 7256-7305, 2016 | 40* | 2016 |
| Metric learning for temporal sequence alignment D Garreau, R Lajugie, S Arlot, F Bach Advances in neural information processing systems, 1817-1825, 2014 | 40 | 2014 |
| Multi-task regression using minimal penalties M Solnon, S Arlot, F Bach Journal of Machine Learning Research 13 (Sep), 2773-2812, 2012 | 34 | 2012 |
| Estimating the accuracy of satellite ephemerides using the bootstrap method J Desmars, S Arlot, JE Arlot, V Lainey, A Vienne Astronomy & Astrophysics 499 (1), 321-330, 2009 | 26 | 2009 |
| Consistent change-point detection with kernels D Garreau, S Arlot Electronic Journal of Statistics 12 (2), 4440-4486, 2018 | 25 | 2018 |
| Choosing a penalty for model selection in heteroscedastic regression S Arlot Arxiv preprint arXiv:0812.3141, 2008 | 22* | 2008 |
| Margin-adaptive model selection in statistical learning S Arlot, PL Bartlett Bernoulli 17 (2), 687-713, 2011 | 18 | 2011 |
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
