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May, 2018
因果判斷彙總下反事實公平的因果模型池化
Pooling of Causal Models under Counterfactual Fairness via Causal Judgement Aggregation
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Fabio Massimo Zennaro, Magdalena Ivanovska
TL;DR
该论文探讨了如何在满足反事实公平性的要求下，结合不同专家提供的多个概率因果模型，提出了两种基于因果公正和因果判断聚合理论的算法，生成符合公平性标准的聚合概率因果模型，并在玩具案例研究中比较了它们的行为。
Abstract
In this paper we consider the problem of combining multiple
probabilistic causal models
, provided by different experts, under the requirement that the aggregated model satisfy the criterion of
counterfactual fairness
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