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Asymptotic Properties of Bayes Risk of a General Class of Shrinkage
  Priors in Multiple Hypothesis Testing Under Sparsity
v1v2v3v4v5v6 (latest)

Asymptotic Properties of Bayes Risk of a General Class of Shrinkage Priors in Multiple Hypothesis Testing Under Sparsity

28 October 2013
P. Ghosh
Xueying Tang
M. Ghosh
A. Chakrabarti
ArXiv (abs)PDFHTML

Papers citing "Asymptotic Properties of Bayes Risk of a General Class of Shrinkage Priors in Multiple Hypothesis Testing Under Sparsity"

16 / 16 papers shown
Title
Time-varying Factor Augmented Vector Autoregression with Grouped Sparse Autoencoder
Yiyong Luo
Brooks Paige
Jim Griffin
CML
80
0
0
06 Mar 2025
Asymptotic Bayes Optiamlity for Sparse Count Data
Asymptotic Bayes Optiamlity for Sparse Count Data
Sayantan Paul
and Arijit Chakrabarti
15
0
0
11 Jan 2024
A Bayesian approach to estimate the completeness of death registration
A Bayesian approach to estimate the completeness of death registration
Jairo Fúquene Patino
Tim Adair
19
0
0
03 Oct 2023
Posterior Contraction rate and Asymptotic Bayes Optimality for one-group
  shrinkage priors in sparse normal means problem
Posterior Contraction rate and Asymptotic Bayes Optimality for one-group shrinkage priors in sparse normal means problem
Sayantan Paul
A. Chakrabarti
27
0
0
04 Nov 2022
Identifiable Deep Generative Models via Sparse Decoding
Identifiable Deep Generative Models via Sparse Decoding
Gemma E. Moran
Dhanya Sridhar
Yixin Wang
David M. Blei
BDL
118
49
0
20 Oct 2021
On Posterior consistency of Bayesian Changepoint models
On Posterior consistency of Bayesian Changepoint models
Nilabja Guha
J. Datta
43
0
0
25 Feb 2021
Horseshoe Regularization for Machine Learning in Complex and Deep Models
Horseshoe Regularization for Machine Learning in Complex and Deep Models
A. Bhadra
J. Datta
Yunfan Li
Nicholas G. Polson
84
15
0
24 Apr 2019
Log-Scale Shrinkage Priors and Adaptive Bayesian Global-Local Shrinkage
  Estimation
Log-Scale Shrinkage Priors and Adaptive Bayesian Global-Local Shrinkage Estimation
Daniel F. Schmidt
E. Makalic
18
1
0
08 Jan 2018
Risk quantification for the thresholding rule for multiple testing using
  Gaussian scale mixtures
Risk quantification for the thresholding rule for multiple testing using Gaussian scale mixtures
J. Salomond
81
9
0
23 Nov 2017
Uncertainty quantification for the horseshoe
Uncertainty quantification for the horseshoe
S. V. D. Pas
Botond Szabó
A. van der Vaart
94
74
0
07 Jul 2016
Prediction risk for the horseshoe regression
Prediction risk for the horseshoe regression
A. Bhadra
J. Datta
Yunfan Li
Nicholas G. Polson
Brandon T. Willard
171
16
0
16 May 2016
Some Permutationllay Symmetric Multiple Hypotheses Testing Rules Under
  Dependent Set up
Some Permutationllay Symmetric Multiple Hypotheses Testing Rules Under Dependent Set up
A. Kundu
S. K. Bhandari
39
0
0
13 Apr 2016
Asymptotic Minimaxity, Optimal Posterior Concentration and Asymptotic
  Bayes Optimality of Horseshoe-type Priors Under Sparsity
Asymptotic Minimaxity, Optimal Posterior Concentration and Asymptotic Bayes Optimality of Horseshoe-type Priors Under Sparsity
P. Ghosh
A. Chakrabarti
22
1
0
05 Oct 2015
Bayesian Multiple Testing Under Sparsity for Polynomial-Tailed
  Distributions
Bayesian Multiple Testing Under Sparsity for Polynomial-Tailed Distributions
Xueying Tang
Ke Li
M. Ghosh
32
1
0
27 Sep 2015
The Horseshoe+ Estimator of Ultra-Sparse Signals
The Horseshoe+ Estimator of Ultra-Sparse Signals
A. Bhadra
J. Datta
Nicholas G. Polson
Brandon T. Willard
99
169
0
02 Feb 2015
Posterior Concentration Properties of a General Class of Shrinkage
  Priors around Nearly Black Vectors
Posterior Concentration Properties of a General Class of Shrinkage Priors around Nearly Black Vectors
P. Ghosh
A. Chakrabarti
87
18
0
28 Dec 2014
1