
Asynchronous and Distributed Data Augmentation for Massive Data Settings
Data augmentation (DA) algorithms are widely used for Bayesian inference...
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Geometric ergodicity of Gibbs samplers for the Horseshoe and its regularized variants
The Horseshoe is a widely used and popular continuous shrinkage prior fo...
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BCONCORD – A scalable Bayesian highdimensional precision matrix estimation procedure
Sparse estimation of the precision matrix under highdimensional scaling...
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Estimating accuracy of the MCMC variance estimator: a central limit theorem for batch means estimators
The batch means estimator of the MCMC variance is a simple and effective...
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Consistent Bayesian Sparsity Selection for Highdimensional Gaussian DAG Models with Multiplicative and Betamixture Priors
Estimation of the covariance matrix for highdimensional multivariate da...
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Estimation of Gaussian directed acyclic graphs using partial ordering information with an application to dairy cattle data
Estimating a directed acyclic graph (DAG) from observational data repres...
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A Bayesian Approach to Joint Estimation of Multiple Graphical Models
The problem of joint estimation of multiple graphical models from high d...
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A Hybrid Alternative to Gibbs Sampling for Bayesian Latent Variable Models
Gibbs sampling is a widely popular Markov chain Monte Carlo algorithm wh...
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Trace class Markov chains for the NormalGamma Bayesian shrinkage model
Highdimensional data, where the number of variables exceeds or is compa...
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Consistent estimation of the spectrum of trace class data augmentation algorithms
Markov chain Monte Carlo is widely used in a variety of scientific appli...
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A convex pseudolikelihood framework for high dimensional partial correlation estimation with convergence guarantees
Sparse high dimensional graphical model selection is a topic of much int...
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Kshitij Khare
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