39 citations · 49 across the 10 of their papers we have counts for
3 papers · 1 filter
Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness
Stephen R. Pfohl, Natalie Harris, Chirag Nagpal +12
Disaggregated evaluation across subgroups is critical for assessing the fairness of machine learning models, but its uncritical use can mislead practitioners. We show that equal pe…
Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning
Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara
While machine learning is rapidly being developed and deployed in health settings such as influenza prediction, there are critical challenges in using data from one environment in…
Population-aware Hierarchical Bayesian Domain Adaptation
Vishwali Mhasawade, Nabeel Abdur Rehman, Rumi Chunara
Population attributes are essential in health for understanding who the data represents and precision medicine efforts. Even within disease infection labels, patients can exhibit s…