2 citations · 2 across the 2 of their papers we have counts for
3 papers
RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups
Bum Chul Kwon, Uri Kartoun, Shaan Khurshid +7
Disease risk models can identify high-risk patients and help clinicians provide more personalized care. However, risk models developed on one dataset may not generalize across dive…
Statistical inference for individual fairness
Subha Maity, Songkai Xue, Mikhail Yurochkin +1
As we rely on machine learning (ML) models to make more consequential decisions, the issue of ML models perpetuating or even exacerbating undesirable historical biases (e.g., gende…
Does enforcing fairness mitigate biases caused by subpopulation shift?
Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin +1
Many instances of algorithmic bias are caused by subpopulation shifts. For example, ML models often perform worse on demographic groups that are underrepresented in the training da…