@article{guedj2013,
author = "Guedj, Benjamin and Alquier, Pierre",
doi = "10.1214/13-EJS771",
fjournal = "Electronic Journal of Statistics",
journal = "Electron. J. Statist.",
pages = "264--291",
abstract = "The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption ($p\gg n$ paradigm). A PAC-Bayesian strategy is investigated, delivering oracle inequalities in probability. The implementation is performed through recent outcomes in high-dimensional MCMC algorithms, and the performance of our method is assessed on simulated data.",
publisher = "The Institute of Mathematical Statistics and the Bernoulli Society",
title = {{PAC-Bayesian} estimation and prediction in sparse additive models},
url = "https://doi.org/10.1214/13-EJS771",
volume = "7",
year = "2013",
url_arXiv = "https://arxiv.org/abs/1208.1211",
url_PDF = "https://arxiv.org/pdf/1208.1211.pdf",
url_Code = "https://cran.r-project.org/package=pacbpred",
keywords={mine}
}

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