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Complexity Results for MCMC derived from Quantitative Bounds
v1v2v3v4v5v6 (latest)

Complexity Results for MCMC derived from Quantitative Bounds

2 August 2017
Jun Yang
Jeffrey S. Rosenthal
ArXiv (abs)PDFHTML

Papers citing "Complexity Results for MCMC derived from Quantitative Bounds"

14 / 14 papers shown
Entropy contraction of the Gibbs sampler under log-concavity
Entropy contraction of the Gibbs sampler under log-concavity
Filippo Ascolani
Hugo Lavenant
Giacomo Zanella
491
15
0
01 Oct 2024
Dimension-free Relaxation Times of Informed MCMC Samplers on Discrete Spaces
Dimension-free Relaxation Times of Informed MCMC Samplers on Discrete Spaces
Hyunwoong Chang
Quan Zhou
354
6
0
05 Apr 2024
Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models
Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models
Filippo Ascolani
Gareth O. Roberts
T. Rigon
397
12
0
14 Mar 2024
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
384
3
0
12 Dec 2022
Stereographic Markov Chain Monte Carlo
Stereographic Markov Chain Monte CarloAnnals of Statistics (Ann. Stat.), 2022
Jun Yang
K. Latuszyñski
Gareth O. Roberts
274
16
0
24 May 2022
Convergence rate bounds for iterative random functions using one-shot
  coupling
Convergence rate bounds for iterative random functions using one-shot coupling
Sabrina Sixta
Jeffrey S. Rosenthal
303
1
0
07 Dec 2021
On the convergence rate of the "out-of-order" block Gibbs sampler
On the convergence rate of the "out-of-order" block Gibbs sampler
Z. Jin
J. Hobert
123
1
0
27 Oct 2021
Dimension-free Mixing for High-dimensional Bayesian Variable Selection
Dimension-free Mixing for High-dimensional Bayesian Variable Selection
Quan Zhou
Jun Yang
Dootika Vats
Gareth O. Roberts
Jeffrey S. Rosenthal
255
31
0
12 May 2021
Dimension free convergence rates for Gibbs samplers for Bayesian linear
  mixed models
Dimension free convergence rates for Gibbs samplers for Bayesian linear mixed modelsStochastic Processes and their Applications (SPA), 2021
Z. Jin
J. Hobert
273
5
0
10 Mar 2021
On the limitations of single-step drift and minorization in Markov chain
  convergence analysis
On the limitations of single-step drift and minorization in Markov chain convergence analysisThe Annals of Applied Probability (Ann. Appl. Probab.), 2020
Qian Qin
J. Hobert
284
35
0
21 Mar 2020
An asymptotic Peskun ordering and its application to lifted samplers
An asymptotic Peskun ordering and its application to lifted samplersBernoulli (Bernoulli), 2020
Philippe Gagnon
Florian Maire
445
11
0
11 Mar 2020
Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector
  Autoregressions
Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector AutoregressionsElectronic Journal of Statistics (EJS), 2019
Karl Oskar Ekvall
Galin L. Jones
330
18
0
06 Jul 2019
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
346
9
0
16 Mar 2019
Gibbs posterior convergence and the thermodynamic formalism
Gibbs posterior convergence and the thermodynamic formalism
K. Mcgoff
S. Mukherjee
A. Nobel
314
10
0
24 Jan 2019
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