CAREER: Robust Machine Learning via Principled Defenses against Adversaries and Distribution Shifts

Machine learning (ML) systems have achieved impressive capabilities across domains such as vision, language, and planning. However, even state-of-the-art models can fail dramatically in unpredictable ways, including under minor shifts in data distribution. These failures are exacerbated in the presence of adversaries (i.e., other actors or systems…