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A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality
  Guarantees
v1v2 (latest)

A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees

1 October 2014
M. Chichignoud
Johannes Lederer
Martin J. Wainwright
ArXiv (abs)PDFHTML

Papers citing "A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees"

5 / 5 papers shown
Title
Tuning parameter calibration for $\ell_1$-regularized logistic
  regression
Tuning parameter calibration for ℓ1\ell_1ℓ1​-regularized logistic regression
Wei Li
Johannes Lederer
90
13
0
01 Oct 2016
Oracle Inequalities for High-dimensional Prediction
Oracle Inequalities for High-dimensional Prediction
Johannes Lederer
Lu Yu
Irina Gaynanova
92
24
0
01 Aug 2016
High dimensional regression and matrix estimation without tuning
  parameters
High dimensional regression and matrix estimation without tuning parameters
S. Chatterjee
71
4
0
25 Oct 2015
Optimal Two-Step Prediction in Regression
Optimal Two-Step Prediction in Regression
Didier Chételat
Johannes Lederer
Joseph Salmon
120
19
0
18 Oct 2014
On the Prediction Performance of the Lasso
On the Prediction Performance of the Lasso
A. Dalalyan
Mohamed Hebiri
Johannes Lederer
191
168
0
07 Feb 2014
1