research
∙
04/27/2020
Using reference models in variable selection
Variable selection, or more generally, model reduction is an important a...
share
research
∙
10/21/2019
Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach
A salient approach to interpretable machine learning is to restrict mode...
research
∙
06/20/2019
Pushing the Limits of Importance Sampling through Iterative Moment Matching
The accuracy of an integral approximation via Monte Carlo sampling depen...
research
∙
10/04/2018
Projective Inference in High-dimensional Problems: Prediction and Feature Selection
This paper discusses predictive inference and feature selection for gene...
research
∙
01/17/2018
Bayesian Estimation of Gaussian Graphical Models with Projection Predictive Selection
Gaussian graphical models are used for determining conditional relations...
research
∙
12/21/2017
