PAC-Bayesian Estimation and Prediction in Sparse Additive Models
Methodology
2018-05-22 v3 Statistics Theory
Statistics Theory
Abstract
The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption ( 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.
Cite
@article{arxiv.1208.1211,
title = {PAC-Bayesian Estimation and Prediction in Sparse Additive Models},
author = {Benjamin Guedj and Pierre Alquier},
journal= {arXiv preprint arXiv:1208.1211},
year = {2018}
}
Comments
28 pages