BriefGPT.xyz
May, 2017
贝叶斯公平性
Subjective fairness: Fairness is in the eye of the beholder
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Christos Dimitrakakis, Yang Liu, David Parkes, Goran Radanovic
TL;DR
本文从贝叶斯公平的角度探讨了在决策中如何解决模型不确定性带来的不公平问题，并介绍了将参数不确定性纳入机器学习公平性的新概念。结合Kleinberg等人提出的公平定义，研究表明贝叶斯公平能产生在高度不确定性下性能好的公平决策规则。
Abstract
We analyze different notions of
fairness
in
decision making
when the underlying model is not known with certainty. We argue that recent notions of
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