PAC-Bayesian bounds for sparse regression estimation with exponential weights

From MaRDI portal
Publication:1952177

DOI10.1214/11-EJS601zbMath1274.62463arXiv1009.2707OpenAlexW3123715748MaRDI QIDQ1952177

Karim Lounici, Pierre Alquier

Publication date: 28 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1009.2707



Related Items

Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression, PAC-Bayesian high dimensional bipartite ranking, General Robust Bayes Pseudo-Posteriors: Exponential Convergence Results with Applications, Multiple Kernel Learningの学習理論, Ordered smoothers with exponential weighting, Comments on: ``On active learning methods for manifold data, Exponential weights in multivariate regression and a low-rankness favoring prior, User-friendly Introduction to PAC-Bayes Bounds, Sharp oracle inequalities for aggregation of affine estimators, Simple proof of the risk bound for denoising by exponential weights for asymmetric noise distributions, PAC-Bayesian estimation and prediction in sparse additive models, Upper bounds and aggregation in bipartite ranking, Kullback-Leibler aggregation and misspecified generalized linear models, Concentration inequalities for the exponential weighting method, Aggregation of affine estimators, Estimation and variable selection with exponential weights, Optimal learning with \textit{Q}-aggregation, Structured, Sparse Aggregation, Prediction of time series by statistical learning: general losses and fast rates, Estimation from nonlinear observations via convex programming with application to bilinear regression, Exponential screening and optimal rates of sparse estimation, On some recent advances on high dimensional Bayesian statistics, A quasi-Bayesian perspective to online clustering, Sparse estimation by exponential weighting, On the exponentially weighted aggregate with the Laplace prior, A Bayesian approach for noisy matrix completion: optimal rate under general sampling distribution, Robust Bayes estimation using the density power divergence


Uses Software


Cites Work