5 citations · 5 across the 1 of their papers we have counts for
3 papers
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…
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…
The Horseshoe+ Estimator of Ultra-Sparse Signals
Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson +1
We propose a new prior for ultra-sparse signal detection that we term the "horseshoe+ prior." The horseshoe+ prior is a natural extension of the horseshoe prior that has achieved s…