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Optimal upper and lower bounds for the true and empirical excess risks
  in heteroscedastic least-squares regression
v1v2 (latest)

Optimal upper and lower bounds for the true and empirical excess risks in heteroscedastic least-squares regression

24 April 2013
Adrien Saumard
ArXiv (abs)PDFHTML

Papers citing "Optimal upper and lower bounds for the true and empirical excess risks in heteroscedastic least-squares regression"

4 / 4 papers shown
Title
Aggregated hold out for sparse linear regression with a robust loss
  function
Aggregated hold out for sparse linear regression with a robust loss function
G. Maillard
FedML
76
1
0
26 Feb 2020
On optimality of empirical risk minimization in linear aggregation
On optimality of empirical risk minimization in linear aggregation
Adrien Saumard
75
21
0
11 May 2016
Concentration behavior of the penalized least squares estimator
Concentration behavior of the penalized least squares estimator
Alan Muro
Sara van de Geer
51
10
0
27 Nov 2015
Slope heuristics and V-Fold model selection in heteroscedastic
  regression using strongly localized bases
Slope heuristics and V-Fold model selection in heteroscedastic regression using strongly localized bases
F. Navarro
Adrien Saumard
77
16
0
21 May 2015
1