ABSTRACT: Despite the great empirical success of adversarial training to defend deep learning models against adversarial perturbations, so far, it still remains rather unclear what [...]

ABSTRACT: The purpose of this talk is to explain the role of causal inference in the context of growing interests in machine learning and data [...]

ABSTRACT: We consider sequential prediction with expert advice when data are generated from distributions varying arbitrarily within an unknown constraint set. We quantify relaxations of [...]