solidot新版网站常见问题,请点击这里查看。
消息
本文已被查看150次
A Central Limit Theorem for $L_p$ transportation cost with applications to Fairness Assessment in Machine Learning. (arXiv:1807.06796v1 [math.ST])
来源于:arXiv
We provide a Central Limit Theorem for the Monge-Kantorovich distance between
two empirical distributions with size $n$ and $m$, $W_p(P_n,Q_m)$ for $p>1$ for
observations on the real line, using a minimal amount of assumptions. We
provide an estimate of the asymptotic variance which enables to build a two
sample test to assess the similarity between two distributions. This test is
then used to provide a new criterion to assess the notion of fairness of a
classification algorithm. 查看全文>>