8 citations · 8 across the 1 of their papers we have counts for
2 papers
cs.LG2020
Fairness by Explicability and Adversarial SHAP Learning
James M. Hickey, Pietro G. Di Stefano, Vlasios Vasileiou
The ability to understand and trust the fairness of model predictions, particularly when considering the outcomes of unprivileged groups, is critical to the deployment and adoption…
cs.AI2020★ 8 cited
Counterfactual fairness: removing direct effects through regularization
Pietro G. Di Stefano, James M. Hickey, Vlasios Vasileiou
Building machine learning models that are fair with respect to an unprivileged group is a topical problem. Modern fairness-aware algorithms often ignore causal effects and enforce…