Characterizing the Sample Complexity of Semi-Supervised Adversarially Robust PAC Learning

There is a significant benefit in semi-supervised robust learning compared to the supervised setting, with the labeled sample complexity being sharply characterized by a different complexity measure (VCU) rather than the standard VC dimension.