15 citations · 21 across the 4 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
stat.ME2019
Horseshoe Regularization for Machine Learning in Complex and Deep Models
Anindya Bhadra, Jyotishka Datta, Yunfan Li +1
Since the advent of the horseshoe priors for regularization, global-local shrinkage methods have proved to be a fertile ground for the development of Bayesian methodology in machin…
stat.ME2019★ 5 cited
Joint Mean-Covariance Estimation via the Horseshoe with an Application in Genomic Data Analysis
Yunfan Li, Jyotishka Datta, Bruce A. Craig +1
Seemingly unrelated regression is a natural framework for regressing multiple correlated responses on multiple predictors. The model is very flexible, with multiple linear regressi…