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stat.ML2023★ 1 cited
Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates
Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen
Across various sectors such as healthcare, criminal justice, national security, finance, and technology, large-scale machine learning (ML) and artificial intelligence (AI) systems…
stat.ML2023
Data Augmentation via Subgroup Mixup for Improving Fairness
Madeline Navarro, Camille Little, Genevera I. Allen +1
In this work, we propose data augmentation via pairwise mixup across subgroups to improve group fairness. Many real-world applications of machine learning systems exhibit biases ac…