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04/21/2023
Machine Learning and the Future of Bayesian Computation
Bayesian models are a powerful tool for studying complex data, allowing ...
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09/18/2021
Asynchronous and Distributed Data Augmentation for Massive Data Settings
Data augmentation (DA) algorithms are widely used for Bayesian inference...
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08/04/2021
Gaussian Process Regression and Classification using International Classification of Disease Codes as Covariates
International Classification of Disease (ICD) codes are widely used for ...
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05/30/2021
Divide-and-Conquer Bayesian Inference in Hidden Markov Models
Divide-and-conquer Bayesian methods consist of three steps: dividing the...
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05/30/2021
Asymptotic Normality of the Posterior Distributions in a Class of Hidden Markov Models
We show that the posterior distribution of parameters in a hidden Markov...
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06/01/2020
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior
Varying coefficient models (VCMs) are widely used for estimating nonline...
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11/18/2019
A Distributed Algorithm for Polya-Gamma Data Augmentation
The Polya-Gamma data augmentation (PG-DA) algorithm is routinely used fo...
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06/20/2018
An Asynchronous Distributed Expectation Maximization Algorithm For Massive Data: The DEM Algorithm
The family of Expectation-Maximization (EM) algorithms provides a genera...
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12/28/2017