17 citations · 22 across the 3 of their papers we have counts for
3 papers · 1 filter
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics
Shu Hu, George H. Chen
We propose a general approach for training survival analysis models that minimizes a worst-case error across all subpopulations that are large enough (occurring with at least a use…
Counterfactual Predictions under Runtime Confounding
Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova
Algorithms are commonly used to predict outcomes under a particular decision or intervention, such as predicting whether an offender will succeed on parole if placed under minimal…
Counterfactual Risk Assessments, Evaluation, and Fairness
Amanda Coston, Alan Mishler, Edward H. Kennedy +1
Algorithmic risk assessments are increasingly used to help humans make decisions in high-stakes settings, such as medicine, criminal justice and education. In each of these cases,…