RobustAugMix: Joint Optimization of Natural and Adversarial Robustness

Josue Martinez-Martinez, Olivia Brown

Abstract: Machine learning models often suffer performance degradation when faced with corrupted data. In this work, we explore a technique that combines a data augmentation strategy (AugMix) with adversarial training, in order to increase robustness to both natural and adversarial forms of data corruption.