Thèmes de recherche
- Apprentissage statistique
- Statistique non paramétrique
Encadrement doctoral
- Alexandre Borel (2023 - …)
- Audrey Poterie (2015 - 2018)
- Nedjmeddine Allab (2013 - 2016)
- Clément Vital (2013 - 2016)
Publications
Dieumegard, A., Dufresne, S., Richard, C., Orfila, L., Martin, B., Rouvière, L., Oliveira, A., Croyal, M., Mathieu, R. et Rébillard, A. (2025). Structured Treadmill Training as a Strategy to Mitigate Tumor Growth and Preserve Adipose tissue and Muscle Strength in Prostate Tumor Bearing Mice, Medicine and Science in Sports and Exercise, Vol. 10, DOI:<10.1249/MSS.0000000000003675>.
Klutchnikoff, N., Poterie, A. et Rouvière, L. (2022). Statistical analysis of a hierarchical clustering algorithm with outliers, Journal of Multivariate Analysis, Vol.192, DOI:<10.1016/j.jmva.2022.105075>.
Dufresne, S., Richard, C., Dieumegard, A., Orfila, L., Delpon, G., Chiavassa, S., Martin, B., Rouvière, L., Escoffre, J.M., Oujagir, E., de Senneville, B.D., Bouakaz, A., Rioux-Leclerq, N., Potiron, V. et Rébillard, A (2021). Voluntary Wheel Running Does Not Enhance Radiotherapy Efficiency in a Preclinical Model of Prostate Cancer: The Importance of Physical Activity Modalities? Cancers, Vol. 13(21), DOI:<10.3390/cancers13215402>.
De Müllenheim, P.Y., Rouvière, L. , Emily, M., Chaudru, E., Kaladji, A., Mahé, G. et Le Faucheur, A (2021). Shoud I stay or should I go now?” Recovery time effect on walking capacity in symptomatic peripheral artery disease. Journal of applied physiology. Vol. 131(1), 207-219. DOI:<10.1152/japplphysiol.00441.2020>.
A. Poterie, J.F. Dupuy, V. Monbet et L. Rouvière (2019). Classification tree algorithm for grouped variables. Computational statistics. Vol. 34, pp. 1613-1648. DOI:<10.1007/s00180-019-00894-y>.
G. Biau, B. Cadre et L. Rouvière (2019). Accelerated gradient boosting. Machine Learning, Vol. 19, pp. 971-992. Télécharger AGB. DOI:<10.1007/s10994-019-05787-1>.
N. Hengartner, E. Matzner-Løber, L. Rouvière et T. Burr (2018). Multiplicative bias corrected nonparametric smoothers. In Nonparametric statistics, Springer proceedings in Mathematics and Statistics, 3rd ISNPS, Avignon, 2016. DOI:<10.1007/978-3-319-96941-1_3>.
S. Auray, N. Klutchnikoff et L. Rouvière (2015). On clustering procedure and nonparametric mixture estimation. Electronic Journal of Statistics, Vol. 9, pp. 266-297. DOI:<10.1214/15-EJS995>.
T. Burr, N. Hengartner, E. Matzner-Løber, S. Myers et L. Rouvière (2011), Smoothing Low Resolution Spectral Data. IEEE Transactions on Nuclear Science, Vol. 57, pp. 2831–2840. DOI:<10.1109/TNS.2010.2054110>.
G. Biau, B. Cadre et L. Rouvière (2010). Statistical analysis of k-nearest neighbor collaborative recommendation. The Annals of Statistics, Vol. 38, pp. 1568–1592.DOI:<10.1214/09-AOS759>.
G. Biau, O. Biau et L. Rouvière (2008). Nonparametric forecasting of the manufacturing output growth with firm-level survey data. Journal of Business Cycle Measurement and Analysis, Vol. 3 , pp. 317–332. DOI:<10.1787/17293626>.
A. Berlinet, G. Biau et L. Rouvière (2008). Functional classification with wavelets. Annales de l’ISUP, Vol. 52, pp. 61–80.
L. Rouvière (2006). Sélection d’histogrammes modifiés itérés. Journal de la Société Française de Statistique, Vol. 147 , pp. 65–83.
A. Berlinet, G. Biau et L. Rouvière (2005). Optimal \(L_1\) bandwidth selection for variable kernel density estimates. Statistics and Probability Letters, Vol. 74, pp. 116–128. DOI:<10.1016/j.spl.2005.04.036>.
A. Berlinet, G. Biau et L. Rouvière (2005). Parameter selection in modified histogram estimates. Statistics, Vol. 39 , pp. 91–105. DOI:<10.1080/02331880500059713>.
A. Berlinet et L. Rouvière (2005). Effective construction of modified histograms in higher dimensions. In Statistical Modeling and Analysis for Complex Data Problems, ed P. Duchesne et B. Rémillard. DOI:<10.1007/0-387-24555-3_6>.