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Generalization of l1 constraints for high dimensional regression
  problems

Generalization of l1 constraints for high dimensional regression problems

1 November 2008
Pierre Alquier
Mohamed Hebiri
ArXivPDFHTML

Papers citing "Generalization of l1 constraints for high dimensional regression problems"

7 / 7 papers shown
Title
On the conditions used to prove oracle results for the Lasso
On the conditions used to prove oracle results for the Lasso
Sara van de Geer
Peter Buhlmann
272
732
0
05 Oct 2009
The Dantzig selector and sparsity oracle inequalities
The Dantzig selector and sparsity oracle inequalities
V. Koltchinskii
248
134
0
04 Sep 2009
Sparse recovery in convex hulls via entropy penalization
Sparse recovery in convex hulls via entropy penalization
V. Koltchinskii
128
32
0
13 May 2009
Consistent selection via the Lasso for high dimensional approximating
  regression models
Consistent selection via the Lasso for high dimensional approximating regression models
F. Bunea
157
43
0
21 May 2008
High-dimensional generalized linear models and the lasso
High-dimensional generalized linear models and the lasso
Sara van de Geer
627
756
0
04 Apr 2008
Sup-norm convergence rate and sign concentration property of Lasso and
  Dantzig estimators
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
Karim Lounici
453
242
0
30 Jan 2008
LASSO, Iterative Feature Selection and the Correlation Selector: Oracle
  Inequalities and Numerical Performances
LASSO, Iterative Feature Selection and the Correlation Selector: Oracle Inequalities and Numerical Performances
Pierre Alquier
98
15
0
24 Oct 2007
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