Minimax AUC Fairness: Efficient Algorithm with Provable Convergence. (arXiv:2208.10451v1 [cs.LG])

The use of machine learning models in consequential decision making often
exacerbates societal inequity, in particular yielding disparate impact on
members of marginalized groups defined by race and gender. The area under the
ROC curve (AUC) is widely used to evaluate the performance of a scoring
function in machine learning, but is studied in algorithmic fairness less than
other performance metrics. Due to the pairwise nature of the AUC, defining an
AUC-based group fairness metric is pairwise-dependent and may involve …

algorithm arxiv auc convergence fairness lg minimax