Web: http://arxiv.org/abs/2206.09868

Sept. 16, 2022, 1:15 a.m. | Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Prateek Mittal, Haitao Zheng

cs.CV updates on arXiv.org arxiv.org

Representation learning, i.e. the generation of representations useful for
downstream applications, is a task of fundamental importance that underlies
much of the success of deep neural networks (DNNs). Recently, robustness to
adversarial examples has emerged as a desirable property for DNNs, spurring the
development of robust training methods that account for adversarial examples.
In this paper, we aim to understand how the properties of representations
learned by robust training differ from those obtained from standard, non-robust
training. This is critical …

arxiv representation understanding

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