FADE: FAir Double Ensemble Learning for Observable and Counterfactual OutcomesJan 1, 2022·Alan Mishler,Edward H. Kennedy· 0 min read Cite URL arXivTypeConference paperPublicationProceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT)Last updated on Jan 1, 2022 AuthorsAlan MishlerAI Research Lead/VP ← Counterfactual Mean-Variance Optimization Jan 1, 2022Fair When Trained, Unfair When Deployed: Observable Fairness Measures are Unstable in Performative Prediction Settings Jan 1, 2022 →
