10 citations · 13 across the 7 of their papers we have counts for
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stat.ME2023
Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
Jianqing Fan, Xin Tong, Yanhui Wu +2
Organizations often rely on statistical algorithms to make socially and economically impactful decisions. We must address the fairness issues in these important automated decisions…
stat.ME2016★ 3 cited
Testing mutual independence in high dimension via distance covariance
Shun Yao, Xianyang Zhang, Xiaofeng Shao
In this paper, we introduce a type test for testing mutual independence and banded dependence structure for high dimensional data. The test is constructed based on…