【Google】深度学习对抗鲁棒性，43页ppt

最新深度学习对抗鲁棒性教程

  • 深度学习基础 Deep learning essentials

  • 对抗扰动 Introduction to adversarial perturbations

    • Simple Projected Gradient Descent-based attacks

    • Targeted Projected Gradient Descent-based attacks

    • Fast Gradient Sign Method (FGSM) attacks

    • Natural [8]

    • Synthetic [1, 2]

  • Optimizer susceptibility w.r.t to different attacks 优化器对不同攻击的敏感性w.r.

  • 对抗学习 Adversarial learning

    • Training on a dataset perturbed with FGSM

    • Training with Neural Structured Learning [3]

  • Improving adversarial performance with EfficientNet [4] and its variants like Noisy Student Training [5] and AdvProp [6]

https://github.com/dipanjanS/adversarial-learning-robustness

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