| A survey of cross-validation procedures for model selection S Arlot, A Celisse Statistics Surveys 4, 40-79, 2010 | 4764 | 2010 |
| Data-driven calibration of penalties for least-squares regression S Arlot, P Massart The Journal of Machine Learning Research 10, 245-279, 2009 | 222 | 2009 |
| A kernel multiple change-point algorithm via model selection S Arlot, A Celisse, Z Harchaoui Journal of machine learning research 20 (162), 1-56, 2019 | 207* | 2019 |
| Choice of V for V-fold cross-validation in least-squares density estimation S Arlot, M Lerasle Journal of Machine Learning Research 17 (208), 1-50, 2016 | 158* | 2016 |
| Analysis of purely random forests bias S Arlot, R Genuer arXiv preprint arXiv:1407.3939, 2014 | 111 | 2014 |
| Consistent change-point detection with kernels D Garreau, S Arlot | 95 | 2018 |
| V-fold cross-validation improved: V-fold penalization S Arlot Arxiv preprint arXiv:0802.0566, 2008 | 89* | 2008 |
| Resampling and model selection S Arlot | 89* | 2007 |
| A survey of cross-validation procedures for model selection. Stat Surv 4: 40–79 S Arlot, A Celisse | 86 | 2010 |
| Segmentation of the mean of heteroscedastic data via cross-validation S Arlot, A Celisse Arxiv preprint arXiv:0902.3977, 2009 | 86 | 2009 |
| Model selection by resampling penalization S Arlot Electronic Journal of Statistics 3, 557-624, 2009 | 84 | 2009 |
| Metric learning for temporal sequence alignment D Garreau, R Lajugie, S Arlot, F Bach Advances in neural information processing systems 27, 2014 | 71 | 2014 |
| Data-driven calibration of linear estimators with minimal penalties S Arlot, F Bach Arxiv preprint arXiv:0909.1884, 2009 | 71* | 2009 |
| Large-margin metric learning for constrained partitioning problems R Lajugie, F Bach, S Arlot International Conference on Machine Learning, 297-305, 2014 | 66* | 2014 |
| 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 | 64 | 2009 |
| 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 | 58 | 2010 |
| Minimal penalties and the slope heuristics: a survey S Arlot Journal de la société française de statistique 160 (3), 1-106, 2019 | 57 | 2019 |
| Multi-task regression using minimal penalties M Solnon, S Arlot, F Bach The Journal of Machine Learning Research 13 (1), 2773-2812, 2012 | 40 | 2012 |
| Margin-adaptive model selection in statistical learning S Arlot, PL Bartlett Bernoulli 17 (2), 687-713, 2011 | 32 | 2011 |
| Some nonasymptotic results on resampling in high dimension, II: Multiple tests S Arlot, G Blanchard, E Roquain The Annals of Statistics 38 (1), 83-99, 2010 | 32 | 2010 |
Alain CelisseSAMM Laboratory - Paris 1 Panthéon-Sorbonne University在 univ-paris1.fr 的电子邮件经过验证
