CMMR: A Composite Multidimensional Models Robustness Evaluation Framework for Deep Learning

Author:

Liu Wanyi,Zhang Shigeng,Wang Weiping,Zhang Jian,Liu Xuan

Publisher

Springer Nature Singapore

Reference41 articles.

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3. Jin, G., Yi, X., Huang, W., Schewe, S., Huang, X.: Enhancing adversarial training with second-order statistics of weights. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 15273–15283 (2022)

4. Zhang, H., Yu, Y., Jiao, J., Xing, E., El Ghaoui, L., Jordan, M.: Theoretically principled trade-off between robustness and accuracy. In: International Conference on Machine Learning, pp. 7472–7482. PMLR (2019)

5. Carlini, N., Wagner, D.: Defensive distillation is not robust to adversarial examples. arXiv preprint arXiv:1607.04311 (2016)

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