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Choosing a penalty for model selection in heteroscedastic regression
v1v2 (latest)

Choosing a penalty for model selection in heteroscedastic regression

16 December 2008
Sylvain Arlot
ArXiv (abs)PDFHTML

Papers citing "Choosing a penalty for model selection in heteroscedastic regression"

7 / 7 papers shown
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
419
16
0
21 May 2015
Log-concavity and strong log-concavity: a review
Log-concavity and strong log-concavity: a reviewStatistics Survey (SS), 2014
Adrien Saumard
J. Wellner
535
314
0
23 Apr 2014
Model selection and estimation of a component in additive regression
Model selection and estimation of a component in additive regression
X. Gendre
297
15
0
28 Sep 2012
The Slope Heuristics in Heteroscedastic Regression
The Slope Heuristics in Heteroscedastic Regression
Adrien Saumard
615
8
0
06 Apr 2011
Model selection by resampling penalization
Model selection by resampling penalization
Sylvain Arlot
500
66
0
17 Jun 2009
Segmentation of the mean of heteroscedastic data via cross-validation
Segmentation of the mean of heteroscedastic data via cross-validation
Sylvain Arlot
Alain Celisse
OOD
386
67
0
23 Feb 2009
Data-driven calibration of penalties for least-squares regression
Data-driven calibration of penalties for least-squares regressionJournal of machine learning research (JMLR), 2008
Sylvain Arlot
P. Massart
784
162
0
06 Feb 2008
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