A robust, adaptive M-estimator for pointwise estimation in
heteroscedastic regression

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A robust, adaptive M-estimator for pointwise estimation in heteroscedastic regression

18 July 2012

Johannes Lederer

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Papers citing "A robust, adaptive M-estimator for pointwise estimation in heteroscedastic regression"

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Title
Risk Bounds for Robust Deep Learning Johannes Lederer OOD 59 16 0 14 Sep 2020
Mean estimation and regression under heavy-tailed distributions--a survey Gabor Lugosi S. Mendelson 105 246 0 10 Jun 2019
Learning from MOM's principles: Le Cam's approach Lecué Guillaume Lerasle Matthieu 117 52 0 08 Jan 2017
Optimal Two-Step Prediction in Regression Didier Chételat Johannes Lederer Joseph Salmon 120 19 0 18 Oct 2014
A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees M. Chichignoud Johannes Lederer Martin J. Wainwright 103 13 0 01 Oct 2014
Adaptation to lowest density regions with application to support recovery Tim Patschkowski Angelika Rohde 137 17 0 18 Aug 2014
Adaptive estimation over anisotropic functional classes via oracle approach O. Lepski 99 35 0 18 May 2014
Bandwidth selection in kernel empirical risk minimization via the gradient M. Chichignoud S. Loustau 84 1 0 27 Jan 2014
Adaptive Noisy Clustering M. Chichignoud S. Loustau 55 10 0 10 Jun 2013