4 citations · 5 across the 2 of their papers we have counts for
3 papers
Bayesian variable selection in linear regression models with instrumental variables
Gautam Sabnis, Yves Atchadé, Prosper Dovonon
Many papers on high-dimensional statistics have proposed methods for variable selection and inference in linear regression models by relying explicitly or implicitly on the assumpt…
Compressed Covariance Estimation With Automated Dimension Learning
Gautam Sabnis, Debdeep Pati, Anirban Bhattacharya
We propose a method for estimating a covariance matrix that can be represented as a sum of a low-rank matrix and a diagonal matrix. The proposed method compresses high-dimensional…
A Divide and Conquer Strategy for High Dimensional Bayesian Factor Models
Gautam Sabnis, Debdeep Pati, Barbara Engelhardt +1
We propose a distributed computing framework, based on a divide and conquer strategy and hierarchical modeling, to accelerate posterior inference for high-dimensional Bayesian fact…