Increasing concerns have been raised on deep learning fairness in recent years. Existing fairness-aware machine learning methods mainly focus on the fairness of in-distribution data. However, in real-world applications, it is common to have …
Instead of isolated properties, we target on a holistic trustworthiness covering every properties in one solution.
A distributed domain/group debiasing framework for unsupervised domain adaptation or fairness enhancement.