@article{AIHPB_2004__40_6_685_0, author = {Audibert, Jean-Yves}, title = {Aggregated estimators and empirical complexity for least square regression}, journal = {Annales de l'I.H.P. Probabilit\'es et statistiques}, pages = {685--736}, publisher = {Elsevier}, volume = {40}, number = {6}, year = {2004}, doi = {10.1016/j.anihpb.2003.11.006}, mrnumber = {2096215}, zbl = {1052.62037}, language = {en}, url = {http://www.numdam.org/articles/10.1016/j.anihpb.2003.11.006/} }
TY - JOUR AU - Audibert, Jean-Yves TI - Aggregated estimators and empirical complexity for least square regression JO - Annales de l'I.H.P. Probabilités et statistiques PY - 2004 SP - 685 EP - 736 VL - 40 IS - 6 PB - Elsevier UR - http://www.numdam.org/articles/10.1016/j.anihpb.2003.11.006/ DO - 10.1016/j.anihpb.2003.11.006 LA - en ID - AIHPB_2004__40_6_685_0 ER -
%0 Journal Article %A Audibert, Jean-Yves %T Aggregated estimators and empirical complexity for least square regression %J Annales de l'I.H.P. Probabilités et statistiques %D 2004 %P 685-736 %V 40 %N 6 %I Elsevier %U http://www.numdam.org/articles/10.1016/j.anihpb.2003.11.006/ %R 10.1016/j.anihpb.2003.11.006 %G en %F AIHPB_2004__40_6_685_0
Audibert, Jean-Yves. Aggregated estimators and empirical complexity for least square regression. Annales de l'I.H.P. Probabilités et statistiques, Tome 40 (2004) no. 6, pp. 685-736. doi : 10.1016/j.anihpb.2003.11.006. http://www.numdam.org/articles/10.1016/j.anihpb.2003.11.006/
[1] Bagging predictors, Machine Learning 24 (2) (1996) 123-140. | Zbl
,[2] Arcing classifiers, Ann. Statist 26 (3) (1998) 801-849. | MR | Zbl
,[3] O. Catoni, Statistical Learning Theory and Stochastic Optimization, in: Probability Summer School, Saint Flour, 2001, Springer-Verlag, submitted for publication. | MR | Zbl
[4] Experiments with a new boosting algorithm, in: Machine Learning: Proceedings of the Thirteenth International Conference, 1996, pp. 148-156.
, ,[5] J. Friedman, T. Hastie, R. Tibshirani, Additive logistic regression: a statistical view of boosting, Technical Report, Dept. of Statistics, Stanford University, 1998.
[6] Functional aggregation for nonparametric estimation, Ann. Statist 28 (2000) 681-712. | MR | Zbl
, ,[7] Smooth discrimination analysis, Ann. Statist 27 (1999) 1808-1829. | MR | Zbl
, ,[8] PAC-bayesian stochastic model selection, Machine Learning J (2001), submitted for publication. | Zbl
,[9] Lectures on Probability Theory and Statistics. Part II: Topics in Non-Parametric Statistics, in: Probability Summer School, Saint Flour, Springer-Verlag, Berlin, 1998. | MR | Zbl
,[10] Barrier boosting, in: Proc. COLT'00, Morgan Kaufmann, Palo Alto, 2000, pp. 170-179.
, , , , , ,[11] R.E. Schapire, Y. Singer, Improved boosting algorithms using confidence-rated predictions, 1998, pp. 80-91.
[12] A.B. Tsybakov, Optimal aggregation of classifiers in statistical learning, 2001.
[13] Y. Yang, Aggregating regression procedures for a better performance, 2001.
Cité par Sources :