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Perturbation theory for Markov chains via Wasserstein distance

Perturbation theory for Markov chains via Wasserstein distance

13 March 2015
Daniel Rudolf
Nikolaus Schweizer
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Papers citing "Perturbation theory for Markov chains via Wasserstein distance"

10 / 10 papers shown
Title
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
Umut Simsekli
Mert Gurbuzbalaban
S. Yıldırım
Lingjiong Zhu
30
2
0
04 Mar 2024
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic
  Gradient Descent
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
Lingjiong Zhu
Mert Gurbuzbalaban
Anant Raj
Umut Simsekli
19
6
0
20 May 2023
Reversibility of elliptical slice sampling revisited
Reversibility of elliptical slice sampling revisited
Mareike Hasenpflug
Viacheslav Natarovskii
Daniel Rudolf
17
5
0
06 Jan 2023
Geometric convergence of elliptical slice sampling
Geometric convergence of elliptical slice sampling
Viacheslav Natarovskii
Daniel Rudolf
Björn Sprungk
13
11
0
07 May 2021
Scalable Bayesian computation for crossed and nested hierarchical models
Scalable Bayesian computation for crossed and nested hierarchical models
O. Papaspiliopoulos
Timothée Stumpf-Fétizon
Giacomo Zanella
18
10
0
19 Mar 2021
Central limit theorems for Markov chains based on their convergence
  rates in Wasserstein distance
Central limit theorems for Markov chains based on their convergence rates in Wasserstein distance
Rui Jin
Aixin Tan
18
6
0
21 Feb 2020
Informed Sub-Sampling MCMC: Approximate Bayesian Inference for Large
  Datasets
Informed Sub-Sampling MCMC: Approximate Bayesian Inference for Large Datasets
Florian Maire
Nial Friel
Pierre Alquier
30
14
0
26 Jun 2017
Bayes Shrinkage at GWAS scale: Convergence and Approximation Theory of a
  Scalable MCMC Algorithm for the Horseshoe Prior
Bayes Shrinkage at GWAS scale: Convergence and Approximation Theory of a Scalable MCMC Algorithm for the Horseshoe Prior
J. Johndrow
Paulo Orenstein
A. Bhattacharya
29
23
0
02 May 2017
Quantifying the accuracy of approximate diffusions and Markov chains
Quantifying the accuracy of approximate diffusions and Markov chains
Jonathan H. Huggins
James Y. Zou
36
29
0
20 May 2016
Stability of Noisy Metropolis-Hastings
Stability of Noisy Metropolis-Hastings
F. Medina-Aguayo
Anthony Lee
Gareth O. Roberts
51
41
0
24 Mar 2015
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