Kiran Krishnamachari

ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity

Adversarial attacks pose a major challenge for modern deep neural networks. Recent advancements show that adversarially robust generalization requires a large amount of labeled data for training. If annotation becomes a burden, can unlabeled data help bridge the gap? In this paper, we propose ARMOUR…