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On the Computational Complexity of High-Dimensional Bayesian Variable
  Selection

On the Computational Complexity of High-Dimensional Bayesian Variable Selection

29 May 2015
Yun Yang
Martin J. Wainwright
Michael I. Jordan
ArXivPDFHTML

Papers citing "On the Computational Complexity of High-Dimensional Bayesian Variable Selection"

17 / 17 papers shown
Title
Lower bounds on the rate of convergence for accept-reject-based Markov
  chains in Wasserstein and total variation distances
Lower bounds on the rate of convergence for accept-reject-based Markov chains in Wasserstein and total variation distances
Austin R. Brown
Galin L. Jones
24
3
0
12 Dec 2022
Scalable Spike-and-Slab
Scalable Spike-and-Slab
N. Biswas
Lester W. Mackey
Xiao-Li Meng
GP
35
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
35
1
0
14 Mar 2022
Order-based Structure Learning without Score Equivalence
Order-based Structure Learning without Score Equivalence
Hyunwoong Chang
James Cai
Quan Zhou
CML
OffRL
29
3
0
10 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
21
18
0
28 Jan 2022
Approximate Laplace approximations for scalable model selection
Approximate Laplace approximations for scalable model selection
D. Rossell
Oriol Abril
A. Bhattacharya
19
15
0
14 Dec 2020
Reversible Jump PDMP Samplers for Variable Selection
Reversible Jump PDMP Samplers for Variable Selection
Augustin Chevallier
Paul Fearnhead
Matthew Sutton
21
18
0
22 Oct 2020
Model Based Screening Embedded Bayesian Variable Selection for
  Ultra-high Dimensional Settings
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings
Dongjin Li
Somak Dutta
Vivekananda Roy
6
11
0
13 Jun 2020
Monte Carlo Approximation of Bayes Factors via Mixing with Surrogate
  Distributions
Monte Carlo Approximation of Bayes Factors via Mixing with Surrogate Distributions
Chenguang Dai
Jun S. Liu
23
7
0
12 Sep 2019
Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector
  Autoregressions
Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector Autoregressions
Karl Oskar Ekvall
Galin L. Jones
16
16
0
06 Jul 2019
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
Targeted Random Projection for Prediction from High-Dimensional Features
Targeted Random Projection for Prediction from High-Dimensional Features
Minerva Mukhopadhyay
David B. Dunson
23
15
0
06 Dec 2017
Complexity Results for MCMC derived from Quantitative Bounds
Complexity Results for MCMC derived from Quantitative Bounds
Jun Yang
Jeffrey S. Rosenthal
31
23
0
02 Aug 2017
Bayesian Sparse Linear Regression with Unknown Symmetric Error
Bayesian Sparse Linear Regression with Unknown Symmetric Error
Minwoo Chae
Lizhen Lin
David B. Dunson
33
15
0
06 Aug 2016
The Future of Data Analysis in the Neurosciences
The Future of Data Analysis in the Neurosciences
D. Bzdok
B. Yeo
AI4CE
16
5
0
05 Aug 2016
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
45
57
0
06 Jun 2015
Convergence rate of Markov chain methods for genomic motif discovery
Convergence rate of Markov chain methods for genomic motif discovery
D. Woodard
Jeffrey S. Rosenthal
60
16
0
12 Mar 2013
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