@inproceedings{24f3482231884bfda1ea92e9b182abb9,
title = "Pac-bayesian aggregation of affine estimators",
abstract = "Aggregating estimators using exponential weights depending on their risk appears optimal in expectation but not in probability. We use here a slight overpenalization to obtain oracle inequality in probability for such an explicit aggregation procedure. We focus on the fixed design regression framework and the aggregation of linear estimators and obtain results for a large family of linear estimators under a non-necessarily independent sub-Gaussian noise assumptions.",
author = "L. Montuelle and \{Le Pennec\}, E.",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 3rd Conference of the International Society for Nonparametric Statistics, ISNPS 2016 ; Conference date: 11-06-2016 Through 16-06-2016",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/978-3-319-96941-1\_9",
language = "English",
isbn = "9783319969404",
series = "Springer Proceedings in Mathematics and Statistics",
publisher = "Springer New York LLC",
pages = "133--144",
editor = "Patrice Bertail and Delphine Blanke and Pierre-Andr{\'e} Cornillon and Eric Matzner-L{\o}ber",
booktitle = "Nonparametric Statistics- 3rd ISNPS 2016",
}