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cs.LG2025
Targeted Learning for Inference on Data Fairness
Alexander Asemota, Joseph H. Rudoler, Giles Hooker
As algorithmic decision making has become increasingly ubiquitous even in high-stakes settings, significant effort has been invested in defining, detecting, and eliminating unfair…
cs.LG2024
Longitudinal Counterfactuals: Constraints and Opportunities
Alexander Asemota, Giles Hooker
Counterfactual explanations are a common approach to providing recourse to data subjects. However, current methodology can produce counterfactuals that cannot be achieved by the su…