Nearly optimal Bayesian Shrinkage for High Dimensional Regression

24 December 2017

Papers citing "Nearly optimal Bayesian Shrinkage for High Dimensional Regression"

28 / 28 papers shown

Title
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R Xingguo Li T. Zhao Xiaoming Yuan Han Liu 39 74 0 27 Jun 2020
Bayesian Shrinkage towards Sharp Minimaxity Qifan Song 23 7 0 11 Apr 2020
Adaptive posterior contraction rates for the horseshoe S. V. D. Pas Botond Szabó A. van der Vaart 40 70 0 13 Feb 2017
Uncertainty quantification for the horseshoe S. V. D. Pas Botond Szabó A. van der Vaart 64 73 0 07 Jul 2016
Prediction risk for the horseshoe regression A. Bhadra J. Datta Yunfan Li Nicholas G. Polson Brandon T. Willard 122 16 0 16 May 2016
A General Framework for Bayes Structured Linear Models Chao Gao A. van der Vaart Harrison H. Zhou 256 57 0 06 Jun 2015
On the Computational Complexity of High-Dimensional Bayesian Variable Selection Yun Yang Martin J. Wainwright Michael I. Jordan 100 151 0 29 May 2015
Posterior Concentration Properties of a General Class of Shrinkage Priors around Nearly Black Vectors P. Ghosh A. Chakrabarti 40 18 0 28 Dec 2014
Sure Screening for Gaussian Graphical Models Shuang Luo R. Song Daniela Witten 51 23 0 29 Jul 2014
Empirical Bayes posterior concentration in sparse high-dimensional linear models Ryan Martin Raymond Mess S. Walker 162 103 0 30 Jun 2014
Bayesian variable selection with shrinking and diffusing priors N. Narisetty Xuming He BDL 83 212 0 26 May 2014
The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors S. V. D. Pas B. Kleijn A. van der Vaart 71 169 0 01 Apr 2014
Bayesian linear regression with sparse priors I. Castillo Johannes Schmidt-Hieber A. van der Vaart 151 379 0 04 Mar 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 104 908 0 17 Feb 2014
Dirichlet-Laplace priors for optimal shrinkage A. Bhattacharya D. Pati Natesh S. Pillai David B. Dunson 89 440 0 21 Jan 2014
On asymptotically optimal confidence regions and tests for high-dimensional models Sara van de Geer Peter Buhlmann Yaácov Ritov Ruben Dezeure 191 1,130 0 03 Mar 2013
A significance test for the lasso R. Lockhart Jonathan E. Taylor Robert Tibshirani Robert Tibshirani 239 658 0 30 Jan 2013
Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences I. Castillo A. van der Vaart 118 251 0 06 Nov 2012
Posterior contraction in sparse Bayesian factor models for massive covariance matrices D. Pati A. Bhattacharya Natesh S. Pillai David B. Dunson 94 101 0 16 Jun 2012
Generalized Beta Mixtures of Gaussians Artin Armagan David B. Dunson M. Clyde 84 153 0 25 Jul 2011
Posterior consistency in linear models under shrinkage priors Artin Armagan David B. Dunson Jaeyong Lee W. Bajwa Nate Strawn 58 32 0 20 Apr 2011
Generalized double Pareto shrinkage Artin Armagan David B. Dunson Jaeyong Lee 78 374 0 05 Apr 2011
Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem James G. Scott J. Berger 132 582 0 10 Nov 2010
Bernstein von Mises Theorems for Gaussian Regression with increasing number of regressors D. Bontemps 106 74 0 07 Sep 2010
Nearly unbiased variable selection under minimax concave penalty Cun-Hui Zhang 323 3,557 0 25 Feb 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 214 575 0 11 Oct 2009
Bayesian variable selection for high dimensional generalized linear models: convergence rates of the fitted densities Wenxin Jiang 409 93 0 18 Oct 2007
Convergence rates of posterior distributions for noniid observations S. Ghosal A. van der Vaart 329 396 0 03 Aug 2007