Translator Disclaimer
2017 Estimation of Kullback-Leibler losses for noisy recovery problems within the exponential family
Charles-Alban Deledalle
Electron. J. Statist. 11(2): 3141-3164 (2017). DOI: 10.1214/17-EJS1321

Abstract

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.

Citation

Download Citation

Charles-Alban Deledalle. "Estimation of Kullback-Leibler losses for noisy recovery problems within the exponential family." Electron. J. Statist. 11 (2) 3141 - 3164, 2017. https://doi.org/10.1214/17-EJS1321

Information

Received: 1 May 2016; Published: 2017
First available in Project Euclid: 29 August 2017

zbMATH: 1373.62126
MathSciNet: MR3694579
Digital Object Identifier: 10.1214/17-EJS1321

Subjects:
Primary: 62F10, 62G05
Secondary: 62J12

JOURNAL ARTICLE
24 PAGES


SHARE
Vol.11 • No. 2 • 2017
Back to Top