Exploiting multi-core architectures for reduced-variance estimation with intractable likelihoods

DOI10.1214/15-BA948zbMath1357.62112arXiv1408.4663MaRDI QIDQ516453

Chris J. Oates, Nial Friel, Antonietta Mira

Publication date: 14 March 2017

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1408.4663

zbMATH Keywords

parallel computingMCMCcontrol variateszero variance

Mathematics Subject Classification ID

Related Items (7)

Scalable Control Variates for Monte Carlo Methods Via Stochastic Optimization ⋮ Efficient MCMC for Gibbs random fields using pre-computation ⋮ Bayesian model selection for high-dimensional Ising models, with applications to educational data ⋮ Particle methods for stochastic differential equation mixed effects models ⋮ Noisy Hamiltonian Monte Carlo for Doubly Intractable Distributions ⋮ Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC ⋮ Control variates for stochastic gradient MCMC

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