, PAC-Bayesian bounds for sparse regression estimation with exponential weights, Electronic Journal of Statistics, vol.5, issue.0, pp.127-145, 2010.
DOI : 10.1214/11-EJS601
URL : https://hal.archives-ouvertes.fr/hal-00465801
, Shape Quantization and Recognition with Randomized Trees, Neural Computation, vol.1, issue.1, pp.1545-1588, 1997.
DOI : 10.1016/0031-3203(90)90098-6
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.5478
, Data-driven calibration of linear estimators with minimal penalties, NIPS, pp.46-54, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00414774
, Fast learning rates in statistical inference through aggregation, The Annals of Statistics, vol.37, issue.4, pp.1591-1646, 2009.
DOI : 10.1214/08-AOS623
URL : https://hal.archives-ouvertes.fr/hal-00139030
, Consistency of the group lasso and multiple kernel learning, J. Mach. Learn. Res, vol.9, pp.1179-1225, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00164735
, Estimator selection in the gaussian setting. submitted, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00502156
, Risk bounds for model selection via penalization. Probab. Theory Related Fields, pp.301-413, 1999.
, Bagging predictors, Machine Learning, vol.10, issue.2, pp.123-140, 1996.
DOI : 10.1007/BF00058655
, A Review of Image Denoising Algorithms, with a New One, Multiscale Modeling & Simulation, vol.4, issue.2, pp.490-530, 2005.
DOI : 10.1137/040616024
URL : https://hal.archives-ouvertes.fr/hal-00271141
, Aggregation for Gaussian regression, The Annals of Statistics, vol.35, issue.4, pp.1674-1697, 2007.
DOI : 10.1214/009053606000001587
URL : http://arxiv.org/abs/0710.3654
, inequality approach, The Annals of Statistics, vol.27, issue.3, pp.898-924, 1999.
DOI : 10.1214/aos/1018031262
, Statistical learning theory and stochastic optimization, Lecture Notes in Mathematics, vol.1851, 2004.
DOI : 10.1007/b99352
URL : https://hal.archives-ouvertes.fr/hal-00104952
, Oracle inequalities for inverse problems, The Annals of Statistics, vol.30, issue.3, pp.843-874, 2002.
DOI : 10.1214/aos/1028674843
, All Admissible Linear Estimates of the Mean Vector, The Annals of Mathematical Statistics, vol.37, issue.2, pp.458-463, 1966.
DOI : 10.1214/aoms/1177699528
, Sharp oracle inequalities for aggregation of affine estimators, The Annals of Statistics, vol.40, issue.4, 2011.
DOI : 10.1214/12-AOS1038SUPP
URL : https://hal.archives-ouvertes.fr/hal-00587225
, Aggregation by Exponential Weighting and Sharp Oracle Inequalities, Learning theory, pp.97-111, 2007.
DOI : 10.1007/978-3-540-72927-3_9
URL : https://hal.archives-ouvertes.fr/hal-00160857
, Aggregation by exponential weighting, sharp PAC-Bayesian bounds and sparsity, Machine Learning, vol.52, issue.1-2, pp.39-61, 2008.
DOI : 10.1007/s10994-008-5051-0
URL : https://hal.archives-ouvertes.fr/hal-00291504
, Sparse regression learning by aggregation and Langevin Monte-Carlo, COLT, 2009.
DOI : 10.1016/j.jcss.2011.12.023
URL : https://hal.archives-ouvertes.fr/hal-00362471
, Ideal spatial adaptation by wavelet shrinkage, Biometrika, vol.81, issue.3, pp.425-455, 1994.
DOI : 10.1093/biomet/81.3.425
, Adapting to Unknown Smoothness via Wavelet Shrinkage, Journal of the American Statistical Association, vol.31, issue.432, pp.1200-1224, 1995.
DOI : 10.1080/01621459.1979.10481038
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.8697
, On nonparametric regression for IID observations in a general setting, The Annals of Statistics, vol.24, issue.3, pp.1125-1144, 1996.
DOI : 10.1214/aos/1032526960
, A self-training algorithm for nonparametric filtering, Avtomat. i Telemekh, vol.1, issue.11, pp.58-65, 1984.
, Sharp-optimal and adaptive estimation for heteroscedastic nonparametric regression, Statist. Sinica, vol.6, issue.4, pp.925-942, 1996.
, Boosting a weak learning algorithm by majority, Proceedings of the third annual workshop on Computational learning theory, COLT, pp.202-216, 1990.
, Minimax Multiple Shrinkage Estimation, The Annals of Statistics, vol.14, issue.1, pp.188-205, 1986.
DOI : 10.1214/aos/1176349849
, Mixing least-squares estimators when the variance is unknown, Bernoulli, vol.14, issue.4, pp.1089-1107, 2008.
, Nonparametric estimation of smooth densities of a distribution in L_2, Problemy Peredachi Informatsii, vol.28, issue.1, pp.52-62, 1992.
, On universal oracle inequalities related to high-dimensional linear models, The Annals of Statistics, vol.38, issue.5, pp.2751-2780, 2010.
DOI : 10.1214/10-AOS803
, Functional aggregation for nonparametric regression, Ann. Statist, vol.28, issue.3, pp.681-712, 2000.
, Nonparametric denoising of signals with unknown local structure, I: Oracle inequalities, Applied and Computational Harmonic Analysis, vol.27, issue.2, pp.157-179, 2009.
DOI : 10.1016/j.acha.2009.02.001
URL : https://hal.archives-ouvertes.fr/hal-00318084
, Learning the kernel matrix with semidefinite programming, J. Mach. Learn. Res, vol.5, pp.27-7204, 2003.
, Optimal rates of aggregation in classification under low noise assumption, Bernoulli, vol.13, issue.4, pp.1000-1022, 2007.
DOI : 10.3150/07-BEJ6044
, Information Theory and Mixing Least-Squares Regressions, IEEE Transactions on Information Theory, vol.52, issue.8, 2004.
DOI : 10.1109/TIT.2006.878172
, Information Theory and Mixing Least-Squares Regressions, IEEE Transactions on Information Theory, vol.52, issue.8, pp.3396-3410, 2006.
DOI : 10.1109/TIT.2006.878172
, Generalized mirror averaging and D-convex aggregation, Mathematical Methods of Statistics, vol.16, issue.3, pp.246-259, 2007.
DOI : 10.3103/S1066530707030040
URL : https://hal.archives-ouvertes.fr/hal-00204674
, Topics in non-parametric statistics, volume 1738 of Lecture Notes in Math, 2000.
, Optimal filtration of square-integrable signals in Gaussian noise, Probl. Peredachi Inf, vol.16, issue.2, pp.52-68, 1980.
, Linear and convex aggregation of density estimators, Math. Methods Statist, vol.16, issue.3, pp.260-280, 2007.
, Exponential screening and optimal rates of sparse estimation, Ann. Statist, vol.39, issue.2, pp.731-471, 2011.
, NL-Means and aggregation procedures, 2009 16th IEEE International Conference on Image Processing (ICIP), pp.2977-2980, 2009.
DOI : 10.1109/ICIP.2009.5414512
, An introduction to support vector machines : and other kernel-based learning methods, 2000.
, Estimation of the Mean of a Multivariate Normal Distribution, The Annals of Statistics, vol.9, issue.6, pp.1135-1151, 1981.
DOI : 10.1214/aos/1176345632
, Optimal Rates of Aggregation, COLT, pp.303-313, 2003.
DOI : 10.1007/978-3-540-45167-9_23
URL : https://hal.archives-ouvertes.fr/hal-00104867
, Introduction to nonparametric estimation, 2009.
DOI : 10.1007/b13794
, Combining Different Procedures for Adaptive Regression, Journal of Multivariate Analysis, vol.74, issue.1, pp.135-161, 2000.
DOI : 10.1006/jmva.1999.1884
, Regression with multiple candidate models: selecting or mixing? Statist, Sinica, vol.13, issue.3, pp.783-809, 2003.
, Aggregating regression procedures to improve performance, Bernoulli, vol.10, issue.1, pp.25-47, 2004.
DOI : 10.3150/bj/1077544602
, Model selection and estimation in regression with grouped variables, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.58, issue.1, pp.49-67, 2006.
DOI : 10.1198/016214502753479356
, Information-theoretic upper and lower bounds for statistical estimation, IEEE Transactions on Information Theory, vol.52, issue.4, pp.1307-1321, 2006.
DOI : 10.1109/TIT.2005.864439