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A unified approach to model selection and sparse recovery using
  regularized least squares

A unified approach to model selection and sparse recovery using regularized least squares

21 May 2009
Jinchi Lv
Yingying Fan
ArXivPDFHTML

Papers citing "A unified approach to model selection and sparse recovery using regularized least squares"

5 / 5 papers shown
Title
Rejoinder: One-step sparse estimates in nonconcave penalized likelihood
  models
Rejoinder: One-step sparse estimates in nonconcave penalized likelihood models
H. Zou
Runze Li
222
1,233
0
07 Aug 2008
Discussion: A tale of three cousins: Lasso, L2Boosting and Dantzig
Discussion: A tale of three cousins: Lasso, L2Boosting and Dantzig
N. Meinshausen
G. Rocha
B. Yu
181
73
0
21 Mar 2008
Variable selection in semiparametric regression modeling
Variable selection in semiparametric regression modeling
Runze Li
Hua Liang
84
300
0
13 Mar 2008
Simultaneous analysis of Lasso and Dantzig selector
Simultaneous analysis of Lasso and Dantzig selector
Peter J. Bickel
Yaácov Ritov
Alexandre B. Tsybakov
346
2,527
0
07 Jan 2008
Enhancing Sparsity by Reweighted L1 Minimization
Enhancing Sparsity by Reweighted L1 Minimization
Emmanuel J. Candes
M. Wakin
Stephen P. Boyd
165
5,027
0
10 Nov 2007
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