【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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