MCMC-Based Inference in the Era of Big Data: A Fundamental Analysis of
the Convergence Complexity of High-Dimensional Chains

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MCMC-Based Inference in the Era of Big Data: A Fundamental Analysis of the Convergence Complexity of High-Dimensional Chains

5 August 2015

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Papers citing "MCMC-Based Inference in the Era of Big Data: A Fundamental Analysis of the Convergence Complexity of High-Dimensional Chains"

19 / 19 papers shown

Title
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 70 3 0 12 Dec 2022
Geometric ergodicity of Gibbs samplers for Bayesian error-in-variable regression Austin R. Brown 45 0 0 17 Sep 2022
Convergence rate bounds for iterative random functions using one-shot coupling Sabrina Sixta Jeffrey S. Rosenthal 98 1 0 07 Dec 2021
Exact Convergence Analysis for Metropolis-Hastings Independence Samplers in Wasserstein Distances Austin R. Brown Galin L. Jones 53 7 0 19 Nov 2021
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation D. Yao S. Mclaughlin Y. Altmann 35 6 0 04 Oct 2021
Dimension free convergence rates for Gibbs samplers for Bayesian linear mixed models Z. Jin J. Hobert 47 4 0 10 Mar 2021
On the convergence complexity of Gibbs samplers for a family of simple Bayesian random effects models Bryant Davis J. Hobert 36 3 0 29 Apr 2020
On the limitations of single-step drift and minorization in Markov chain convergence analysis Qian Qin J. Hobert 51 32 0 21 Mar 2020
Central limit theorems for Markov chains based on their convergence rates in Wasserstein distance Rui Jin Aixin Tan 57 6 0 21 Feb 2020
Bayesian Inference for Large Scale Image Classification Jonathan Heek Nal Kalchbrenner UQCV BDL 133 35 0 09 Aug 2019
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random Transport L. Duan OT 61 11 0 24 Jul 2019
Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector Autoregressions Karl Oskar Ekvall Galin L. Jones 48 18 0 06 Jul 2019
Optimal Scaling of Random-Walk Metropolis Algorithms on General Target Distributions Jun Yang Gareth O. Roberts Jeffrey S. Rosenthal OT 95 29 0 27 Apr 2019
Fast Markov chain Monte Carlo for high dimensional Bayesian regression models with shrinkage priors Rui Jin Aixin Tan 58 8 0 16 Mar 2019
A Bayesian Perspective of Statistical Machine Learning for Big Data R. Sambasivan Sourish Das S. Sahu BDL GP 60 20 0 09 Nov 2018
Spectral gaps and error estimates for infinite-dimensional Metropolis-Hastings with non-Gaussian priors Bamdad Hosseini J. Johndrow 63 8 0 30 Sep 2018
Convergence complexity analysis of Albert and Chib's algorithm for Bayesian probit regression Qian Qin J. Hobert 53 32 0 24 Dec 2017
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net T. Michoel 44 1 0 25 Sep 2017
Complexity Results for MCMC derived from Quantitative Bounds Jun Yang Jeffrey S. Rosenthal 84 24 0 02 Aug 2017