TL;DR本文提出了一种基于 Mann Whitney U 统计量的公平性学习方法,用于多任务回归模型的训练,通过非凸的优化和个体排名函数的分组排名功能的定义来提高性能。实验结果验证了本方法的出色表现。
Abstract
In this work, we develop a novel fairness learning approach for multi-task
regression models based on a biased training dataset, using a popular
rank-based non-parametric independence test, i.e., mann whitney u statisti