4 papers
Reasonable uncertainty: Confidence intervals in empirical Bayes discrimination detection
Jiaying Gu, Nikolaos Ignatiadis, Azeem M. Shaikh
We revisit empirical Bayes discrimination detection, focusing on uncertainty arising from both partial identification and sampling variability. While prior work has mostly focused…
Empirical Bayes shrinkage (mostly) does not correct the measurement error in regression
Jiafeng Chen, Jiaying Gu, Soonwoo Kwon
In the value-added literature, it is often claimed that regressing on empirical Bayes shrinkage estimates corrects for the measurement error problem in linear regression. We clarif…
Deep Trees for (Un)structured Data: Tractability, Performance, and Interpretability
Dimitris Bertsimas, Lisa Everest, Jiayi Gu +2
Decision Trees have remained a popular machine learning method for tabular datasets, mainly due to their interpretability. However, they lack the expressiveness needed to handle hi…
Empirical Bayes for the Reluctant Frequentist
Roger Koenker, Jiaying Gu
Empirical Bayes methods offer valuable tools for a large class of compound decision problems. In this tutorial we describe some basic principles of the empirical Bayes paradigm str…