Conformalized Fairness via Quantile Regression. (arXiv:2210.02015v1 [stat.ML])

Algorithmic fairness has received increased attention in socially sensitive
domains. While rich literature on mean fairness has been established, research
on quantile fairness remains sparse but vital. To fulfill great needs and
advocate the significance of quantile fairness, we propose a novel framework to
learn a real-valued quantile function under the fairness requirement of
Demographic Parity with respect to sensitive attributes, such as race or
gender, and thereby derive a reliable fair prediction interval. Using optimal
transport and functional synchronization …

arxiv fairness quantile regression