Assessing AI Fairness in Finance
McCalman, Lachlan, Daniel Steinberg, Grace Abuhamad, Marc-Etienne Brunet, Robert C Williamson, and Richard Zemel. 2022. “Assessing AI Fairness in Finance”. Computer 55 (1): 94-97.
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Information Processing Equalities and the Information-Risk Bridge
Williamson, Robert C, and Zac Cranko. 2024. “Information Processing Equalities and the Information-Risk Bridge”. Journal of Machine Learning Research.
Fairness and Randomness in Machine Learning: Statistical Independence and Relativization
Derr, Rabanus, and Robert C Williamson. 2024. “Fairness and Randomness in Machine Learning: Statistical Independence and Relativization”. The New England Journal of Statistics in Data Science.
What killed the Convex Booster?
Mansour, Yishay, Richard Nock, and Robert C Williamson. 2022. “What Killed the Convex Booster?”. ArXiv Preprint ArXiv:2205.09628.
Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity
Fröhlich, Christian, and Robert C Williamson. 2023. “Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity”. Transactions on Machine Learning Research.
Risk Measures and Upper Probabilities: Coherence and Stratification
Fröhlich, Christian, and Robert C Williamson. 2024. “Risk Measures and Upper Probabilities: Coherence and Stratification”. Journal of Machine Learning Research 25 (207): 1-100.
The Geometry and Calculus of Losses
Williamson, Robert C, and Zac Cranko. 2023. “The Geometry and Calculus of Losses”. Journal of Machine Learning Research 24 (342): 1-72.