Robustness Certificates Against Adversarial Examples for ReLU Networks
@article{Singla2019RobustnessCA, title={Robustness Certificates Against Adversarial Examples for ReLU Networks}, author={Sahil Singla and Soheil Feizi}, journal={ArXiv}, year={2019}, volume={abs/1902.01235} }
While neural networks have achieved high performance in different learning tasks, their accuracy drops significantly in the presence of small adversarial perturbations to inputs. Defenses based on regularization and adversarial training are often followed by new attacks to defeat them. In this paper, we propose attack-agnostic robustness certificates for a multi-label classification problem using a deep ReLU network. Although computing the exact distance of a given input sample to the…
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