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Sub-optimality of some continuous shrinkage priors

Sub-optimality of some continuous shrinkage priors

18 May 2016
A. Bhattacharya
David B. Dunson
D. Pati
Natesh S. Pillai
ArXiv (abs)PDFHTML

Papers citing "Sub-optimality of some continuous shrinkage priors"

15 / 15 papers shown
Title
The Horseshoe Estimator: Posterior Concentration around Nearly Black
  Vectors
The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors
S. V. D. Pas
B. Kleijn
A. van der Vaart
102
169
0
01 Apr 2014
Bayesian linear regression with sparse priors
Bayesian linear regression with sparse priors
I. Castillo
Johannes Schmidt-Hieber
A. van der Vaart
207
382
0
04 Mar 2014
Dirichlet-Laplace priors for optimal shrinkage
Dirichlet-Laplace priors for optimal shrinkage
A. Bhattacharya
D. Pati
Natesh S. Pillai
David B. Dunson
110
441
0
21 Jan 2014
Needles and Straw in a Haystack: Posterior concentration for possibly
  sparse sequences
Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences
I. Castillo
A. van der Vaart
144
252
0
06 Nov 2012
Confidence sets in sparse regression
Confidence sets in sparse regression
Richard Nickl
Sara van de Geer
126
111
0
07 Sep 2012
Posterior contraction in sparse Bayesian factor models for massive
  covariance matrices
Posterior contraction in sparse Bayesian factor models for massive covariance matrices
D. Pati
A. Bhattacharya
Natesh S. Pillai
David B. Dunson
97
101
0
16 Jun 2012
Generalized double Pareto shrinkage
Generalized double Pareto shrinkage
Artin Armagan
David B. Dunson
Jaeyong Lee
114
374
0
05 Apr 2011
Bayes and empirical-Bayes multiplicity adjustment in the
  variable-selection problem
Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
James G. Scott
J. Berger
142
581
0
10 Nov 2010
A Unified Framework for High-Dimensional Analysis of M-Estimators with
  Decomposable Regularizers
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers
S. Negahban
Pradeep Ravikumar
Martin J. Wainwright
Bin Yu
486
1,379
0
13 Oct 2010
Minimax rates of estimation for high-dimensional linear regression over
  $\ell_q$-balls
Minimax rates of estimation for high-dimensional linear regression over ℓq\ell_qℓq​-balls
Garvesh Raskutti
Martin J. Wainwright
Bin Yu
228
575
0
11 Oct 2009
The sparsity and bias of the Lasso selection in high-dimensional linear
  regression
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Cun-Hui Zhang
Jian Huang
474
869
0
07 Aug 2008
Lower bounds for posterior rates with Gaussian process priors
Lower bounds for posterior rates with Gaussian process priors
I. Castillo
123
95
0
17 Jul 2008
Lasso-type recovery of sparse representations for high-dimensional data
Lasso-type recovery of sparse representations for high-dimensional data
N. Meinshausen
Bin Yu
477
882
0
01 Jun 2008
Reproducing kernel Hilbert spaces of Gaussian priors
Reproducing kernel Hilbert spaces of Gaussian priors
Van der Vaart
V. Zanten
101
224
0
21 May 2008
High-dimensional generalized linear models and the lasso
High-dimensional generalized linear models and the lasso
Sara van de Geer
640
755
0
04 Apr 2008
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