Maaya Sakata

Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off

Post-hoc controllability of fair machine learning models, the ability to control the trade-off between fairness and accuracy after training, is valuable for practical deployment. Existing post-processing methods provide such post-hoc controllability but often suffer from significant accuracy degrada…