Estimation of Kullback-Leibler losses for noisy recovery problems within the exponential family
Langue
en
Article de revue
Ce document a été publié dans
Electronic Journal of Statistics. 2017-08-29, vol. 11, n° 2, p. 3141-3164
Shaker Heights, OH : Institute of Mathematical Statistics
Résumé en anglais
We address the question of estimating Kullback-Leibler losses rather than squared losses in recovery problems where the noise is distributed within the exponential family. Inspired by Stein unbiased risk estimator (SURE), ...Lire la suite >
We address the question of estimating Kullback-Leibler losses rather than squared losses in recovery problems where the noise is distributed within the exponential family. Inspired by Stein unbiased risk estimator (SURE), we exhibit conditions under which these losses can be unbiasedly estimated or estimated with a controlled bias. Simulations on parameter selection problems in applications to image denoising and variable selection with Gamma and Poisson noises illustrate the interest of Kullback-Leibler losses and the proposed estimators.< Réduire
Mots clés en anglais
Exponential family
Kullback-Leibler divergence
Model selection
Stein unbiased risk estimator
Origine
Importé de halUnités de recherche