Global-Local Regularization Via Distributional Robustness

1 code implementation • 1 Mar 2022 • Hoang Phan, Trung Le, Trung Phung, Tuan Anh Bui, Nhat Ho, Dinh Phung

First, they purely focus on local regularization to strengthen model robustness, missing a global regularization effect which is useful in many real-world applications (e. g., domain adaptation, domain generalization, and adversarial machine learning).

Domain Generalization

A Unified Wasserstein Distributional Robustness Framework for Adversarial Training

1 code implementation • ICLR 2022 • Tuan Anh Bui, Trung Le, Quan Tran, He Zhao, Dinh Phung

We introduce a new Wasserstein cost function and a new series of risk functions, with which we show that standard AT methods are special cases of their counterparts in our framework.