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.
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