4 citations · 8 across the 11 of their papers we have counts for
16 papers
Bayesian inference on hierarchical nonlocal priors in generalized linear models
Xuan Cao, Kyoungjae Lee
Variable selection methods with nonlocal priors have been widely studied in linear regression models, and their theoretical and empirical performances have been reported. However,…
Consistent and scalable Bayesian joint variable and graph selection for disease diagnosis leveraging functional brain network
Xuan Cao, Kyoungjae Lee
We consider the joint inference of regression coefficients and the inverse covariance matrix for covariates in high-dimensional probit regression, where the predictors are both rel…
Scalable Bayesian high-dimensional local dependence learning
Kyoungjae Lee, Lizhen Lin
In this work, we propose a scalable Bayesian procedure for learning the local dependence structure in a high-dimensional model where the variables possess a natural ordering. The o…
Estimation of Conditional Mean Operator under the Bandable Covariance Structure
Kwangmin Lee, Kyoungjae Lee, Jaeyong Lee
We consider high-dimensional multivariate linear regression models, where the joint distribution of covariates and response variables is a multivariate normal distribution with a b…
The Beta-Mixture Shrinkage Prior for Sparse Covariances with Posterior Minimax Rates
Kyoungjae Lee, Seongil Jo, Jaeyong Lee
Statistical inference for sparse covariance matrices is crucial to reveal dependence structure of large multivariate data sets, but lacks scalable and theoretically supported Bayes…
Post-Processed Posteriors for Banded Covariances
Kwangmin Lee, Kyoungjae Lee, Jaeyong Lee
We consider Bayesian inference of banded covariance matrices and propose a post-processed posterior. The post-processing of the posterior consists of two steps. In the first step,…