Biography
Title
Feature Generating Models: Inference in Purely High Dimensions
Abstract
A new modelling framework for high-dimensional correlation systems is proposed which allows for inference, variable selection, and dimension reduction in the most challenging purely-dimensional asymptotic regime, where sample size is fixed and the number of observed variables grows without bound.