Fair and Optimal Prediction via Post-Processing

Han Zhao

doi:10.1609/aaai.v38i20.30302

Fair and Optimal Prediction via Post-Processing

Authors

Han Zhao University of Illinois Urbana-Champaign

DOI:

https://doi.org/10.1609/aaai.v38i20.30302

Keywords:

Trustworthy Machine Learning, Algorithmic Fairness, Domain Generalization, Robustness

Abstract

In this talk I will discuss our recent work on characterizing the inherent tradeoff between fairness and accuracy in both classification and regression problems. I will also present a post-processing algorithm that derives optimal fair predictors from Bayes score functions.

AAAI-24 / IAAI-24 / EAAI-24 Proceedings Cover

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Published

2024-03-24

How to Cite

Zhao, H. (2024). Fair and Optimal Prediction via Post-Processing. Proceedings of the AAAI Conference on Artificial Intelligence, 38(20), 22686-22686. https://doi.org/10.1609/aaai.v38i20.30302