Missing values are a fundamental problem in data science. Many datasets ...
Many organizations measure treatment effects via an experimentation plat...
Learning heterogeneous treatment effects (HTEs) is an important problem
...
Internet companies are increasingly using machine learning models to cre...
Generalized additive models (GAMs) have become a leading model class for...
Understanding how racial information impacts human decision making in on...
Recent methods for training generalized additive models (GAMs) with pair...
Generalized additive models (GAMs) are favored in many regression and bi...
When might human input help (or not) when assessing risk in fairness-rel...
Model distillation was originally designed to distill knowledge from a l...
Existing methods to estimate the prevalence of chronic hepatitis C (HCV)...
Non-negative matrix factorization (NMF) is a technique for finding laten...
Black-box risk scoring models permeate our lives, yet are typically
prop...