Showing stat.MLShow all
2 papers · 1 filter
stat.ML2026
Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias
Annie Ulichney, Amanda Coston
Understanding how a prediction model will perform in a new environment before deployment is essential to preventing harm when algorithms inform decision-making. Two common sources…
stat.ML2026
The Statistical Fairness-Accuracy Frontier
Alireza Fallah, Michael I. Jordan, Annie Ulichney
We study fairness-accuracy tradeoffs when a single predictive model must serve multiple demographic groups. A useful tool for understanding this tradeoff is the fairness-accuracy (…