Proceedings of Machine Learning Research

Volume 214: Workshop on Algorithmic Fairness through the Lens of Causality and Privacy, 03 December 2022, New Orleans Ernest N. Morial Convention Center, New Orleans, United States of America, hybrid

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

Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt Kusner, Jessica Schrouff; 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

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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

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“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

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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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