4 citations · 7 across the 2 of their papers we have counts for
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cs.LG2022★ 3 cited
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
Edward Small, Wei Shao, Zeliang Zhang +4
With the introduction of machine learning in high-stakes decision making, ensuring algorithmic fairness has become an increasingly important problem to solve. In response to this,…
cs.LG2022★ 4 cited
Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity
Kacper Sokol, Meelis Kull, Jeffrey Chan +1
While data-driven predictive models are a strictly technological construct, they may operate within a social context in which benign engineering choices entail implicit, indirect a…