Sicheng Zhu

Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization

2020 · arXiv (Cornell University)

Training machine learning models that are robust against adversarial inputs poses seemingly insurmountable challenges. To better understand adversarial robustness, we consider the underlying problem of learning robust representations. We develop a notion of representation vulnerability …