Austin Hoag

Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference

Representation learning is increasingly applied to generate representations that generalize well across multiple downstream tasks. Ensuring fairness guarantees in representation learning is crucial to prevent unfairness toward specific demographic groups in downstream tasks. In this work, we formal…