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ORCIDAFCP 2022, New Orleans, LA, USA
- Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff:
Algorithmic Fairness through the Lens of Causality and Privacy Workshop, AFCP 2022, New Orleans, LA, USA (hybrid), 03 December 2022. Proceedings of Machine Learning Research 214, PMLR 2022 - Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff:
Algorithmic Fairness through the Lens of Causality and Privacy (AFCP) 2022. 1-6 - Ruta Binkyte, Karima Makhlouf, Carlos Pinzón, Sami Zhioua, Catuscia Palamidessi:
Causal Discovery for Fairness. 7-22 - Rina Friedberg, Ryan Rogers:
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach. 23-66 - Marc Juarez, Aleksandra Korolova:
“You Can’t Fix What You Can’t Measure”: Privately Measuring Demographic Performance Disparities in Federated Learning. 67-85 - Andrew Lowy, Devansh Gupta, Meisam Razaviyayn:
Stochastic Differentially Private and Fair Learning. 86-119
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