2 citations · 3 across the 5 of their papers we have counts for
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cs.LG2020
Towards Auditability for Fairness in Deep Learning
Ivoline C. Ngong, Krystal Maughan, Joseph P. Near
Group fairness metrics can detect when a deep learning model behaves differently for advantaged and disadvantaged groups, but even models that score well on these metrics can make…
cs.AI2020★ 2 cited
Towards a Measure of Individual Fairness for Deep Learning
Krystal Maughan, Joseph P. Near
Deep learning has produced big advances in artificial intelligence, but trained neural networks often reflect and amplify bias in their training data, and thus produce unfair predi…