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Journal Articles Electronic Journal of Statistics Year : 2013

PAC-Bayesian Estimation and Prediction in Sparse Additive Models

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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.
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Dates and versions

hal-00722969 , version 1 (06-08-2012)
hal-00722969 , version 2 (21-12-2012)
hal-00722969 , version 3 (01-02-2013)

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Benjamin Guedj, Pierre Alquier. PAC-Bayesian Estimation and Prediction in Sparse Additive Models. Electronic Journal of Statistics , 2013, 7, pp.264--291. ⟨10.1214/13-EJS771⟩. ⟨hal-00722969v3⟩
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