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Bayesian linear regression with sparse priors

Bayesian linear regression with sparse priors

4 March 2014
I. Castillo
Johannes Schmidt-Hieber
A. van der Vaart
ArXivPDFHTML

Papers citing "Bayesian linear regression with sparse priors"

41 / 41 papers shown
Title
High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
Tien Mai
34
0
0
13 May 2025
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning
Albert Wilcox
Mohamed Ghanem
Masoud Moghani
Pierre Barroso
Benjamin Joffe
Animesh Garg
50
0
0
06 Mar 2025
Consistency of Graphical Model-based Clustering: Robust Clustering using
  Bayesian Spanning Forest
Consistency of Graphical Model-based Clustering: Robust Clustering using Bayesian Spanning Forest
Yu Zheng
Leo L. Duan
Arkaprava Roy
31
0
0
27 Sep 2024
On high-dimensional classification by sparse generalized Bayesian
  logistic regression
On high-dimensional classification by sparse generalized Bayesian logistic regression
The Tien Mai
46
1
0
19 Mar 2024
Bernstein von-Mises Theorem for g-prior and nonlocal prior
Bernstein von-Mises Theorem for g-prior and nonlocal prior
Xiao Fang
Malay Ghosh
15
0
0
26 Jan 2024
Adaptive Bayesian Predictive Inference in High-dimensional Regerssion
Adaptive Bayesian Predictive Inference in High-dimensional Regerssion
Veronika Rockova
6
0
0
05 Sep 2023
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated
  Learning with Bayesian Inference-Based Adaptive Dropout
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout
Jingjing Xue
Min Liu
Sheng Sun
Yuwei Wang
Hui Jiang
Xue Jiang
18
7
0
14 Jul 2023
Bayesian Inference for $k$-Monotone Densities with Applications to
  Multiple Testing
Bayesian Inference for kkk-Monotone Densities with Applications to Multiple Testing
Kang-Kang Wang
S. Ghosal
14
1
0
08 Jun 2023
Bayesian Analysis for Over-parameterized Linear Model via Effective Spectra
Bayesian Analysis for Over-parameterized Linear Model via Effective Spectra
Tomoya Wakayama
Masaaki Imaizumi
51
1
0
25 May 2023
Empirical Bayes inference in sparse high-dimensional generalized linear
  models
Empirical Bayes inference in sparse high-dimensional generalized linear models
Yiqi Tang
Ryan Martin
30
3
0
14 Mar 2023
Hierarchical shrinkage Gaussian processes: applications to computer code
  emulation and dynamical system recovery
Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery
T. Tang
Simon Mak
David B. Dunson
14
4
0
01 Feb 2023
On the optimization and pruning for Bayesian deep learning
On the optimization and pruning for Bayesian deep learning
X. Ke
Yanan Fan
BDL
UQCV
27
1
0
24 Oct 2022
Sparse high-dimensional linear regression with a partitioned empirical
  Bayes ECM algorithm
Sparse high-dimensional linear regression with a partitioned empirical Bayes ECM algorithm
Alexander C. McLain
A. Zgodic
H. Bondell
31
2
0
16 Sep 2022
Bayesian Sparse Gaussian Mixture Model in High Dimensions
Bayesian Sparse Gaussian Mixture Model in High Dimensions
Dapeng Yao
Fangzheng Xie
Yanxun Xu
31
1
0
21 Jul 2022
Scalable Spike-and-Slab
Scalable Spike-and-Slab
N. Biswas
Lester W. Mackey
Xiao-Li Meng
GP
29
11
0
04 Apr 2022
Bayesian inference on hierarchical nonlocal priors in generalized linear
  models
Bayesian inference on hierarchical nonlocal priors in generalized linear models
Xuan Cao
Kyoungjae Lee
32
1
0
14 Mar 2022
High-dimensional properties for empirical priors in linear regression
  with unknown error variance
High-dimensional properties for empirical priors in linear regression with unknown error variance
X. Fang
M. Ghosh
19
5
0
11 Feb 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview,
  Implementation, and Applications
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
17
18
0
28 Jan 2022
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional
  Gaussian Processes
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes
Hugh Dance
Brooks Paige
GP
20
10
0
08 Nov 2021
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
28
44
0
20 Oct 2021
Performance of Bayesian linear regression in a model with mismatch
Performance of Bayesian linear regression in a model with mismatch
Jean Barbier
Wei-Kuo Chen
D. Panchenko
Manuel Sáenz
40
22
0
14 Jul 2021
Approximate Laplace approximations for scalable model selection
Approximate Laplace approximations for scalable model selection
D. Rossell
Oriol Abril
A. Bhattacharya
16
15
0
14 Dec 2020
Gibbs posterior concentration rates under sub-exponential type losses
Gibbs posterior concentration rates under sub-exponential type losses
Nicholas Syring
Ryan Martin
14
29
0
08 Dec 2020
Spike and slab variational Bayes for high dimensional logistic
  regression
Spike and slab variational Bayes for high dimensional logistic regression
Kolyan Ray
Botond Szabó
Gabriel Clara
40
28
0
22 Oct 2020
Nonasymptotic Laplace approximation under model misspecification
Nonasymptotic Laplace approximation under model misspecification
A. Bhattacharya
D. Pati
13
1
0
16 May 2020
Fast Markov chain Monte Carlo for high dimensional Bayesian regression
  models with shrinkage priors
Fast Markov chain Monte Carlo for high dimensional Bayesian regression models with shrinkage priors
Rui Jin
Aixin Tan
24
8
0
16 Mar 2019
Bayesian Linear Regression for Multivariate Responses Under Group
  Sparsity
Bayesian Linear Regression for Multivariate Responses Under Group Sparsity
Bo Ning
Seonghyun Jeong
S. Ghosal
16
40
0
10 Jul 2018
Nearly optimal Bayesian Shrinkage for High Dimensional Regression
Nearly optimal Bayesian Shrinkage for High Dimensional Regression
Qifan Song
F. Liang
16
76
0
24 Dec 2017
Model Averaging and its Use in Economics
Model Averaging and its Use in Economics
M. Steel
MoMe
16
238
0
24 Sep 2017
Posterior contraction rates for support boundary recovery
Posterior contraction rates for support boundary recovery
M. Reiß
Johannes Schmidt-Hieber
12
4
0
24 Mar 2017
Bayesian Sparse Linear Regression with Unknown Symmetric Error
Bayesian Sparse Linear Regression with Unknown Symmetric Error
Minwoo Chae
Lizhen Lin
David B. Dunson
31
15
0
06 Aug 2016
Uncertainty quantification for the horseshoe
Uncertainty quantification for the horseshoe
S. V. D. Pas
Botond Szabó
A. van der Vaart
30
72
0
07 Jul 2016
Bayesian Variable Selection for Skewed Heteroscedastic Response
Bayesian Variable Selection for Skewed Heteroscedastic Response
Libo Wang
Yuanyuan Tang
D. Sinha
D. Pati
S. Lipsitz
19
3
0
29 Feb 2016
Probabilistic community detection with unknown number of communities
Probabilistic community detection with unknown number of communities
J. Geng
A. Bhattacharya
D. Pati
21
73
0
25 Feb 2016
Needles and straw in a haystack: robust confidence for possibly sparse
  sequences
Needles and straw in a haystack: robust confidence for possibly sparse sequences
E. Belitser
N. Nurushev
22
24
0
05 Nov 2015
A General Framework for Bayes Structured Linear Models
A General Framework for Bayes Structured Linear Models
Chao Gao
A. van der Vaart
Harrison H. Zhou
34
57
0
06 Jun 2015
Optimal Bayesian estimation in stochastic block models
Optimal Bayesian estimation in stochastic block models
D. Pati
A. Bhattacharya
30
7
0
26 May 2015
Gaussian Approximation of General Nonparametric Posterior Distributions
Gaussian Approximation of General Nonparametric Posterior Distributions
Zuofeng Shang
Guang Cheng
31
4
0
13 Nov 2014
A general approach to posterior contraction in nonparametric inverse
  problems
A general approach to posterior contraction in nonparametric inverse problems
B. Knapik
J. Salomond
MedIm
26
32
0
01 Jul 2014
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
40
166
0
01 Apr 2014
Correlated variables in regression: clustering and sparse estimation
Correlated variables in regression: clustering and sparse estimation
Peter Buhlmann
Philipp Rutimann
Sara van de Geer
Cun-Hui Zhang
80
181
0
26 Sep 2012
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