Control Variates for Stochastic Gradient MCMC

Control Variates for Stochastic Gradient MCMC

16 June 2017

Christopher Nemeth

Papers citing "Control Variates for Stochastic Gradient MCMC"

19 / 19 papers shown

Title
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 82 3 0 28 Jan 2025
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 26 0 0 05 Mar 2024
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators B. Leimkuhler Daniel Paulin P. Whalley 23 5 0 14 Jun 2023
Efficient Attention via Control Variates Lin Zheng Jianbo Yuan Chong-Jun Wang Lingpeng Kong 26 18 0 09 Feb 2023
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction Bowen Lei Dongkuan Xu Ruqi Zhang Shuren He Bani Mallick 27 6 0 09 Jan 2023
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 22 15 0 01 Aug 2022
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng Qi Feng G. Karagiannis Guang Lin F. Liang 18 8 0 02 Oct 2020
Federated Stochastic Gradient Langevin Dynamics Khaoula El Mekkaoui Diego Mesquita P. Blomstedt Samuel Kaski FedML 13 24 0 23 Apr 2020
Aggregated Gradient Langevin Dynamics Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 12 1 0 21 Oct 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 16 135 0 16 Jul 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 10 37 0 23 May 2019
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 11 155 0 24 Jul 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 21 31 0 13 Feb 2018
Hamiltonian Monte Carlo with Energy Conserving Subsampling Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran M. Villani 25 62 0 02 Aug 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 31 23 0 02 May 2017
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 32 158 0 21 Oct 2016
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 58 232 0 11 Jul 2016
Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li Sungjin Ahn Max Welling BDL 34 42 0 16 Oct 2015
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,262 0 09 Jun 2012