Uncertainty quantification for sparse Fourier recovery

30 December 2022

Papers citing "Uncertainty quantification for sparse Fourier recovery"

43 / 43 papers shown

Title
Sharp minimax optimality of LASSO and SLOPE under double sparsity assumption Zhifan Li Yanhang Zhang J. Yin 47 4 0 18 Aug 2023
Small Tuning Parameter Selection for the Debiased Lasso Akira Shinkyu N. Sueishi 17 1 0 18 Aug 2022
De-biasing convex regularized estimators and interval estimation in linear models Pierre C. Bellec Cun-Hui Zhang 68 20 0 26 Dec 2019
Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference T. Tony Cai Anru R. Zhang Yuchen Zhou 26 25 0 21 Sep 2019
Unraveling the Veil of Subspace RIP Through Near-Isometry on Subspaces Xingyu Xu Gen Li Yuantao Gu 40 7 0 23 May 2019
De-Biasing The Lasso With Degrees-of-Freedom Adjustment Pierre C. Bellec Cun-Hui Zhang 14 28 0 24 Feb 2019
Greedy Variance Estimation for the LASSO Christopher Kennedy Rachel A. Ward 20 4 0 28 Mar 2018
False Discovery Rate Control via Debiased Lasso Adel Javanmard Hamid Javadi 45 56 0 12 Mar 2018
Inference in high-dimensional graphical models Jana Janková Sara van de Geer 36 65 0 25 Jan 2018
Estimating the error variance in a high-dimensional linear model Guo Yu Jacob Bien 51 39 0 06 Dec 2017
Debiasing the Debiased Lasso with Bootstrap Sai Li 44 14 0 09 Nov 2017
Nonparametric Inference via Bootstrapping the Debiased Estimator Yen-Chi Chen Yen-Chi Chen 21 22 0 22 Feb 2017
Slope meets Lasso: improved oracle bounds and optimality Pierre C. Bellec Guillaume Lecué Alexandre B. Tsybakov 98 189 0 27 May 2016
Direction of arrival estimation using robust complex Lasso Esa Ollila 19 10 0 12 May 2016
On cross-validated Lasso in high dimensions Denis Chetverikov Z. Liao Victor Chernozhukov 61 80 0 07 May 2016
De-biasing the Lasso: Optimal Sample Size for Gaussian Designs Adel Javanmard Andrea Montanari 55 196 0 11 Aug 2015
Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity T. Tony Cai Zijian Guo 131 185 0 18 Jun 2015
A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models Y. Ning Han Liu 77 305 0 30 Dec 2014
Testing and Confidence Intervals for High Dimensional Proportional Hazards Model Ethan X. Fang Y. Ning Han Liu 76 71 0 16 Dec 2014
Asymptotically Honest Confidence Regions for High Dimensional Parameters by the Desparsified Conservative Lasso Mehmet Caner Anders Bredahl Kock 60 70 0 15 Oct 2014
Asymptotic normality and optimalities in estimation of large Gaussian graphical models Zhao Ren Tingni Sun Cun-Hui Zhang Harrison H. Zhou 125 245 0 24 Sep 2013
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Adel Javanmard Andrea Montanari 147 766 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 150 1,130 0 03 Mar 2013
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory Adel Javanmard Andrea Montanari 144 161 0 17 Jan 2013
Stable and robust sampling strategies for compressive imaging Felix Krahmer Rachel A. Ward 80 187 0 08 Oct 2012
Statistical significance in high-dimensional linear models Peter Buhlmann 132 229 0 07 Feb 2012
High-dimensional regression with unknown variance Christophe Giraud S. Huet Nicolas Verzélen 68 62 0 26 Sep 2011
Variable selection with error control: Another look at Stability Selection Rajen Dinesh Shah R. Samworth 71 353 0 27 May 2011
Scaled Sparse Linear Regression Tingni Sun Cun-Hui Zhang 123 507 0 24 Apr 2011
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers S. Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu 274 1,377 0 13 Oct 2010
Templates for Convex Cone Problems with Applications to Sparse Signal Recovery Stephen Becker Emmanuel J. Candès Michael C. Grant 70 680 0 10 Sep 2010
Minimax risks for sparse regressions: Ultra-high-dimensional phenomenons Nicolas Verzélen 209 152 0 03 Aug 2010
$Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls$ Minimax rates of estimation for high-dimensional linear regression over $\ell_q$ -balls Garvesh Raskutti Martin J. Wainwright Bin Yu 156 575 0 11 Oct 2009
On the conditions used to prove oracle results for the Lasso Sara van de Geer Peter Buhlmann 213 729 0 05 Oct 2009
The Benefit of Group Sparsity Junzhou Huang Tong Zhang 151 465 0 20 Jan 2009
P-values for high-dimensional regression N. Meinshausen L. Meier Peter Buhlmann 108 440 0 13 Nov 2008
$On Verifiable Sufficient Conditions for Sparse Signal Recovery via $\ell_1$ Minimization$ On Verifiable Sufficient Conditions for Sparse Signal Recovery via $\ell_1$ Minimization A. Juditsky A. Nemirovski 130 142 0 16 Sep 2008
The sparsity and bias of the Lasso selection in high-dimensional linear regression Cun-Hui Zhang Jian Huang 252 869 0 07 Aug 2008
Lasso-type recovery of sparse representations for high-dimensional data N. Meinshausen Bin Yu 213 879 0 01 Jun 2008
Simultaneous analysis of Lasso and Dantzig selector Peter J. Bickel Yaácov Ritov Alexandre B. Tsybakov 300 2,527 0 07 Jan 2008
On the Distribution of Penalized Maximum Likelihood Estimators: The LASSO, SCAD, and Thresholding B. M. Potscher Hannes Leeb 100 177 0 05 Nov 2007
Sparsity oracle inequalities for the Lasso F. Bunea Alexandre B. Tsybakov M. Wegkamp 305 470 0 23 May 2007
High-dimensional variable selection Larry Wasserman Kathryn Roeder 299 579 0 09 Apr 2007