Trust, but verify: benefits and pitfalls of least-squares refitting in high dimensions

1 June 2013

Papers citing "Trust, but verify: benefits and pitfalls of least-squares refitting in high dimensions"

13 / 13 papers shown

Title
The Group Square-Root Lasso: Theoretical Properties and Fast Algorithms F. Bunea Johannes Lederer Yiyuan She 131 110 0 01 Feb 2013
How Correlations Influence Lasso Prediction Mohamed Hebiri Johannes Lederer 96 102 0 07 Apr 2012
Scaled Sparse Linear Regression Tingni Sun Cun-Hui Zhang 149 507 0 24 Apr 2011
Nuclear norm penalization and optimal rates for noisy low rank matrix completion V. Koltchinskii Alexandre B. Tsybakov Karim Lounici 179 663 0 29 Nov 2010
Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming A. Belloni Victor Chernozhukov Lie Wang 132 672 0 28 Sep 2010
Exponential Screening and optimal rates of sparse estimation Philippe Rigollet Alexandre B. Tsybakov 164 242 0 12 Mar 2010
Least squares after model selection in high-dimensional sparse models A. Belloni Victor Chernozhukov 225 222 0 31 Dec 2009
On the conditions used to prove oracle results for the Lasso Sara van de Geer Peter Buhlmann 230 729 0 05 Oct 2009
$Honest variable selection in linear and logistic regression models via $\ell_1$ and $\ell_1+\ell_2$ penalization$ Honest variable selection in linear and logistic regression models via $\ell_1$ and $\ell_1+\ell_2$ penalization F. Bunea 206 147 0 29 Aug 2008
Lasso-type recovery of sparse representations for high-dimensional data N. Meinshausen Bin Yu 297 879 0 01 Jun 2008
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators Karim Lounici 288 241 0 30 Jan 2008
Simultaneous analysis of Lasso and Dantzig selector Peter J. Bickel Yaácov Ritov Alexandre B. Tsybakov 388 2,527 0 07 Jan 2008
Enhancing Sparsity by Reweighted L1 Minimization Emmanuel J. Candes M. Wakin Stephen P. Boyd 179 5,027 0 10 Nov 2007