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Editors: Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt Kusner, Jessica Schrouff
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Algorithmic Fairness through the Lens of Causality and Privacy (AFCP) 2022
; Proceedings of the Workshop on Algorithmic Fairness through the Lens of Causality and Privacy, PMLR 214:1-6
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Causal Discovery for Fairness
Rūta Binkytė, Karima Makhlouf, Carlos Pinzón, Sami Zhioua, Catuscia Palamidessi; Proceedings of the Workshop on Algorithmic Fairness through the Lens of Causality and Privacy, PMLR 214:7-22
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach
Rina Friedberg, Ryan Rogers; Proceedings of the Workshop on Algorithmic Fairness through the Lens of Causality and Privacy, PMLR 214:23-66
“You Can’t Fix What You Can’t Measure”: Privately Measuring Demographic Performance Disparities in Federated Learning
Marc Juarez, Aleksandra Korolova; Proceedings of the Workshop on Algorithmic Fairness through the Lens of Causality and Privacy, PMLR 214:67-85
Stochastic Differentially Private and Fair Learning
Andrew Lowy, Devansh Gupta, Meisam Razaviyayn; Proceedings of the Workshop on Algorithmic Fairness through the Lens of Causality and Privacy, PMLR 214:86-119
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