De-biasing the Lasso: Optimal Sample Size for Gaussian Designs

11 August 2015

Papers citing "De-biasing the Lasso: Optimal Sample Size for Gaussian Designs"

30 / 30 papers shown

Title
A projection pursuit framework for testing general high-dimensional hypothesis Yinchu Zhu Jelena Bradic 50 13 0 02 May 2017
Linear Hypothesis Testing in Dense High-Dimensional Linear Models Yinchu Zhu Jelena Bradic 89 85 0 10 Oct 2016
Accuracy Assessment for High-dimensional Linear Regression T. Tony Cai Zijian Guo 26 42 0 10 Mar 2016
Honest confidence regions and optimality in high-dimensional precision matrix estimation Jana Janková Sara van de Geer 90 75 0 08 Jul 2015
Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity T. Tony Cai Zijian Guo 152 185 0 18 Jun 2015
SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax Weijie Su Emmanuel Candes 253 145 0 29 Mar 2015
Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach Victor Chernozhukov Christian B. Hansen Martin Spindler 155 174 0 14 Jan 2015
Optimal Inference After Model Selection William Fithian Dennis L. Sun Jonathan E. Taylor 117 335 0 09 Oct 2014
Controlling the false discovery rate via knockoffs Rina Foygel Barber Emmanuel J. Candès 177 746 0 22 Apr 2014
Confidence intervals for high-dimensional inverse covariance estimation Jana Janková Sara van de Geer 106 187 0 26 Mar 2014
Asymptotic behavior of unregularized and ridge-regularized high-dimensional robust regression estimators : rigorous results N. Karoui 54 109 0 11 Nov 2013
Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression Adel Javanmard Andrea Montanari 60 27 0 01 Nov 2013
Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model Mengjie Chen Zhao Ren Hongyu Zhao Harrison H. Zhou 64 59 0 23 Sep 2013
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Adel Javanmard Andrea Montanari 163 766 0 13 Jun 2013
On asymptotically optimal confidence regions and tests for high-dimensional models Sara van de Geer Peter Buhlmann Yaácov Ritov Ruben Dezeure 163 1,130 0 03 Mar 2013
A significance test for the lasso R. Lockhart Jonathan E. Taylor Robert Tibshirani Robert Tibshirani 210 658 0 30 Jan 2013
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory Adel Javanmard Andrea Montanari 146 161 0 17 Jan 2013
Residual variance and the signal-to-noise ratio in high-dimensional linear models Lee H. Dicker 68 5 0 31 Aug 2012
Statistical significance in high-dimensional linear models Peter Buhlmann 145 229 0 07 Feb 2012
Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising D. Donoho Iain M. Johnstone Andrea Montanari 115 179 0 04 Nov 2011
Scaled Sparse Linear Regression Tingni Sun Cun-Hui Zhang 145 507 0 24 Apr 2011
The LASSO risk for gaussian matrices Mohsen Bayati Andrea Montanari 150 317 0 16 Aug 2010
The Noise-Sensitivity Phase Transition in Compressed Sensing D. Donoho A. Maleki Andrea Montanari 85 382 0 08 Apr 2010
Nearly unbiased variable selection under minimax concave penalty Cun-Hui Zhang 294 3,543 0 25 Feb 2010
Least squares after model selection in high-dimensional sparse models A. Belloni Victor Chernozhukov 208 222 0 31 Dec 2009
Message Passing Algorithms for Compressed Sensing D. Donoho A. Maleki Andrea Montanari 100 2,352 0 21 Jul 2009
The sparsity and bias of the Lasso selection in high-dimensional linear regression Cun-Hui Zhang Jian Huang 311 869 0 07 Aug 2008
Simultaneous analysis of Lasso and Dantzig selector Peter J. Bickel Yaácov Ritov Alexandre B. Tsybakov 365 2,527 0 07 Jan 2008
On the "degrees of freedom" of the lasso H. Zou Trevor Hastie Robert Tibshirani 207 1,040 0 06 Dec 2007
High-dimensional variable selection Larry Wasserman Kathryn Roeder 364 579 0 09 Apr 2007