Bibliography (10):

1. A Universal Law of Robustness

2. A Law of Robustness and the Importance of Overparameterization in Deep Learning

3. A law of robustness for two-layers neural networks

4. Towards Deep Learning Models Resistant to Adversarial Attacks

5. Sensitivity and Generalization in Neural Networks: an Empirical Study

6. Intriguing properties of adversarial training at scale

7. Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples

8. ImageNet Large Scale Visual Recognition Challenge

9. Wikipedia Bibliography:

   1. https://en.wikipedia.org/wiki/Perimeter  :

      https://en.wikipedia.org/wiki/Perimeter

   2. MNIST database