$Simultaneous support recovery in high dimensions: Benefits and perils of block $\ell_1/\ell_\infty$-regularization$

Simultaneous support recovery in high dimensions: Benefits and perils of block $\ell_1/\ell_\infty$ -regularization

5 May 2009

Martin J. Wainwright

Papers citing "Simultaneous support recovery in high dimensions: Benefits and perils of block $\ell_1/\ell_\infty$-regularization"

9 / 9 papers shown

Title
Active Learning for Accurate Estimation of Linear Models C. Riquelme Mohammad Ghavamzadeh A. Lazaric 41 11 0 02 Mar 2017
Taking Advantage of Sparsity in Multi-Task Learning Karim Lounici Massimiliano Pontil Alexandre B. Tsybakov Sara van de Geer 265 292 0 09 Mar 2009
The Benefit of Group Sparsity Junzhou Huang Tong Zhang 133 465 0 20 Jan 2009
Support union recovery in high-dimensional multivariate regression G. Obozinski Martin J. Wainwright Michael I. Jordan 171 323 0 05 Aug 2008
Information-theoretic limits on sparse signal recovery: Dense versus sparse measurement matrices Wei Wang Martin J. Wainwright Kannan Ramchandran 64 171 0 03 Jun 2008
Lasso-type recovery of sparse representations for high-dimensional data N. Meinshausen Bin Yu 195 879 0 01 Jun 2008
$On the $\ell_1-\ell_q$ Regularized Regression$ On the $\ell_1-\ell_q$ Regularized Regression Han Liu Jian Zhang 144 18 0 11 Feb 2008
Simultaneous analysis of Lasso and Dantzig selector Peter J. Bickel Yaácov Ritov Alexandre B. Tsybakov 282 2,527 0 07 Jan 2008
Sparse Additive Models Pradeep Ravikumar John D. Lafferty Han Liu Larry A. Wasserman 250 571 0 28 Nov 2007