2024
Feature Importance Disparities for Data Bias Investigations
ICML 2024poster
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection process, or even conducting real-wo…