Pages that link to "Item:Q5231510"

The following pages link to Speeding Up MCMC by Efficient Data Subsampling (Q5231510):

Displaying 45 items.

• Random projections for Bayesian regression (Q144017) (← links)
• Two-stage Metropolis-Hastings for tall data (Q724596) (← links)
• Piecewise deterministic Markov processes for continuous-time Monte Carlo (Q1630397) (← links)
• Subsampling the Gibbs sampler: variance reduction (Q1975358) (← links)
• Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models (Q2066738) (← links)
• Optimal subsampling for least absolute relative error estimators with massive data (Q2099270) (← links)
• Challenges in Markov chain Monte Carlo for Bayesian neural networks (Q2163079) (← links)
• Subsampling sequential Monte Carlo for static Bayesian models (Q2209734) (← links)
• Parallel inference for big data with the group Bayesian method (Q2227203) (← links)
• Subsampling MCMC -- an introduction for the survey statistician (Q2316968) (← links)
• Informed sub-sampling MCMC: approximate Bayesian inference for large datasets (Q2329777) (← links)
• Most likely optimal subsampled Markov chain Monte Carlo (Q2661943) (← links)
• Accelerating Markov chain Monte Carlo with active subspaces (Q2818262) (← links)
• (Q2933948) (← links)
• Bayesian Conditional Density Filtering (Q3391099) (← links)
• Speeding up MCMC by Delayed Acceptance and Data Subsampling (Q3391127) (← links)
• Scalable Bayesian Nonparametric Clustering and Classification (Q3391447) (← links)
• Parallel Markov chain Monte Carlo for Bayesian hierarchical models with big data, in two stages (Q5034158) (← links)
• The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC (Q5066474) (← links)
• An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model (Q5066475) (← links)
• (Q5214185) (← links)
• Stochastic Gradient Markov Chain Monte Carlo (Q5857155) (← links)
• Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators With Massive Data (Q5881082) (← links)
• Mini-Batch Metropolis–Hastings With Reversible SGLD Proposal (Q5881093) (← links)
• How to combine fast heuristic Markov chain Monte Carlo with slow exact sampling (Q5947988) (← links)
• Bayesian computation: a summary of the current state, and samples backwards and forwards (Q5963784) (← links)
• New models for symbolic data analysis (Q6050755) (← links)
• Reflections on Bayesian inference and Markov chain Monte Carlo (Q6059418) (← links)
• Distributed penalized modal regression for massive data (Q6076832) (← links)
• Finding our way in the dark: approximate MCMC for approximate Bayesian methods (Q6121616) (← links)
• Distributed computation for marginal likelihood based model choice (Q6122039) (← links)
• Divide-and-conquer Metropolis-Hastings samplers with matched samples (Q6138717) (← links)
• An efficient adaptive MCMC algorithm for pseudo-Bayesian quantum tomography (Q6177006) (← links)
• Randomized time Riemannian manifold Hamiltonian Monte Carlo (Q6190671) (← links)
• Computing Bayes: from then `til now (Q6540226) (← links)
• Approximating Bayes in the 21st century (Q6540227) (← links)
• Emerging directions in Bayesian computation (Q6540230) (← links)
• An algorithm for distributed Bayesian inference (Q6543846) (← links)
• A review on design inspired subsampling for big data (Q6549149) (← links)
• Hybrid unadjusted Langevin methods for high-dimensional latent variable models (Q6554220) (← links)
• Robust and efficient subsampling algorithms for massive data logistic regression (Q6579821) (← links)
• Bayesian Inference in Common Microeconometric Models With Massive Datasets by Double Marginalized Subsampling (Q6620968) (← links)
• A semi-parametric Bayesian model for semi-continuous longitudinal data (Q6628379) (← links)
• Posterior computation with the Gibbs zig-zag sampler (Q6650959) (← links)
• Contraction rate estimates of stochastic gradient kinetic Langevin integrators (Q6667313) (← links)