BriefGPT.xyz
Dec, 2018
针对个体和群体公平性的偏差缓解后处理
Bias Mitigation Post-processing for Individual and Group Fairness
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Pranay K. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney...
TL;DR
该研究提出了一种新的框架，能够在现实数据集中同时增加个体公平性和群体公平性，并展示了在信用、就业和刑事司法等应用中，在分类准确性、个体和群体公平性方面相比之前的工作表现更为优异。
Abstract
Whereas previous post-processing approaches for increasing the
fairness
of predictions of
biased classifiers
address only group
fairness
,
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