most citedCross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity

19 citations · 26 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2023

Fairness Hub Technical Briefs: AUC Gap

Jinsook Lee, Chris Brooks, Renzhe Yu +1

To measure bias, we encourage teams to consider using AUC Gap: the absolute difference between the highest and lowest test AUC for subgroups (e.g., gender, race, SES, prior knowled…

cs.LG2023★ 19 cited

Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity

Josh Gardner, Renzhe Yu, Quan Nguyen +2

Modern machine learning increasingly supports paradigms that are multi-institutional (using data from multiple institutions during training) or cross-institutional (using models fr…