On Markov chain Monte Carlo methods for tall data

11 May 2015

Chris Holmes

Papers citing "On Markov chain Monte Carlo methods for tall data"

48 / 48 papers shown

Title
Efficient MCMC Sampling with Expensive-to-Compute and Irregular Likelihoods Conor Rosato Harvinder Lehal Simon Maskell L. Devlin Malcolm Strens 19 0 0 15 May 2025
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC F. Llorente Luca Martino Jesse Read D. Delgado OffRL 65 13 0 03 Jan 2025
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics Daniel Paulin P. Whalley Neil K. Chada B. Leimkuhler BDL 49 4 0 14 Oct 2024
Distribution-Aware Mean Estimation under User-level Local Differential Privacy Corentin Pla Hugo Richard Maxime Vono FedML 39 0 0 12 Oct 2024
Minibatch Markov chain Monte Carlo Algorithms for Fitting Gaussian Processes Matthew J. Heaton Jacob A. Johnson 8 1 0 26 Oct 2023
Coreset Markov Chain Monte Carlo Naitong Chen Trevor Campbell 29 4 0 25 Oct 2023
Parameter estimation from an Ornstein-Uhlenbeck process with measurement noise Simon Carter Lilianne Mujica-Parodi H. Strey 41 0 0 22 May 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 45 4 0 21 Apr 2023
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 32 9 0 13 Sep 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 22 15 0 01 Aug 2022
An optimal transport approach for selecting a representative subsample with application in efficient kernel density estimation Jingyi Zhang Cheng Meng Jun Yu Mengrui Zhang Wenxuan Zhong Ping Ma OT 14 12 0 31 May 2022
Bayesian inference via sparse Hamiltonian flows Na Chen Zuheng Xu Trevor Campbell 35 14 0 11 Mar 2022
Variational Inference with Locally Enhanced Bounds for Hierarchical Models Tomas Geffner Justin Domke 26 5 0 08 Mar 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 39 5 0 07 Jan 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 36 26 0 20 Dec 2021
Bounding Wasserstein distance with couplings N. Biswas Lester W. Mackey 22 8 0 06 Dec 2021
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators Zhilin Zhao LongBing Cao Kun-Yu Lin 29 11 0 23 Aug 2021
A Survey of Monte Carlo Methods for Parameter Estimation D. Luengo Luca Martino M. Bugallo Victor Elvira S. Särkkä 21 153 0 25 Jul 2021
Variational Bayes in State Space Models: Inferential and Predictive Accuracy David T. Frazier Rubén Loaiza-Maya G. Martin 11 13 0 23 Jun 2021
Divide-and-Conquer Bayesian Inference in Hidden Markov Models Chunlei Wang Sanvesh Srivastava 30 9 0 30 May 2021
Propensity-to-Pay: Machine Learning for Estimating Prediction Uncertainty M. A. Bashar Kieren Astin-Walmsley Kerina Heath R. Nayak 11 2 0 27 Aug 2020
Model Fusion with Kullback--Leibler Divergence Sebastian Claici Mikhail Yurochkin S. Ghosh Justin Solomon FedML MoMe 18 33 0 13 Jul 2020
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 118 54 0 23 Mar 2020
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 19 134 0 16 Jul 2019
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets Amir-Reza Asadi Emmanuel Abbe BDL AI4CE 34 13 0 26 Jun 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 15 37 0 23 May 2019
Differentially Private Markov Chain Monte Carlo Mikko A. Heikkilä Joonas Jälkö O. Dikmen Antti Honkela 27 25 0 29 Jan 2019
An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics Liangliang Wang Shijia Wang Alexandre Bouchard-Coté 16 32 0 22 Jun 2018
Scalable Bayesian Nonparametric Clustering and Classification Yang Ni Peter Muller M. Diesendruck Sinead Williamson Yitan Zhu Yuan Ji 15 26 0 07 Jun 2018
Accelerating MCMC Algorithms Christian P. Robert Victor Elvira Nicholas G. Tawn Changye Wu 17 140 0 08 Apr 2018
On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms Nicolas García Trillos Zachary T. Kaplan Thabo Samakhoana D. Sanz-Alonso 20 19 0 20 Oct 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 24 32 0 26 Sep 2017
Hamiltonian Monte Carlo with Energy Conserving Subsampling Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran M. Villani 27 62 0 02 Aug 2017
Informed Sub-Sampling MCMC: Approximate Bayesian Inference for Large Datasets Florian Maire Nial Friel Pierre Alquier 33 14 0 26 Jun 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 25 101 0 16 Jun 2017
Bayes Shrinkage at GWAS scale: Convergence and Approximation Theory of a Scalable MCMC Algorithm for the Horseshoe Prior J. Johndrow Paulo Orenstein A. Bhattacharya 34 23 0 02 May 2017
Piecewise Deterministic Markov Processes for Scalable Monte Carlo on Restricted Domains J. Bierkens Alexandre Bouchard-Coté Arnaud Doucet Andrew B. Duncan Paul Fearnhead Thibaut Lienart Gareth O. Roberts Sebastian J. Vollmer 24 55 0 16 Jan 2017
Multilevel Monte Carlo for Scalable Bayesian Computations M. Giles Tigran Nagapetyan Lukasz Szpruch Sebastian J. Vollmer K. Zygalakis 21 9 0 15 Sep 2016
Quasi-stationary Monte Carlo and the ScaLE Algorithm M. Pollock Paul Fearnhead A. M. Johansen Gareth O. Roberts 28 18 0 12 Sep 2016
Joining and splitting models with Markov melding Robert J. B. Goudie A. Presanis David J. Lunn Daniela De Angelis L. Wernisch 25 29 0 22 Jul 2016
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 58 231 0 11 Jul 2016
Coresets for Scalable Bayesian Logistic Regression Jonathan H. Huggins Trevor Campbell Tamara Broderick 24 216 0 20 May 2016
Quantifying the accuracy of approximate diffusions and Markov chains Jonathan H. Huggins James Y. Zou 49 29 0 20 May 2016
The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method Alexandre Bouchard-Coté Sebastian J. Vollmer Arnaud Doucet 29 235 0 08 Oct 2015
Orthogonal parallel MCMC methods for sampling and optimization Luca Martino Victor Elvira D. Luengo J. Corander F. Louzada 37 74 0 30 Jul 2015
Scalable Discrete Sampling as a Multi-Armed Bandit Problem Yutian Chen Zoubin Ghahramani 24 16 0 30 Jun 2015
Perturbation theory for Markov chains via Wasserstein distance Daniel Rudolf Nikolaus Schweizer 40 107 0 13 Mar 2015
Coupled MCMC with a randomized acceptance probability Geoff K. Nicholls C. Fox Alexis Muir Watt 45 41 0 30 May 2012