What are the limitations of adversarial training?

What are the limitations of adversarial training?

Adversarial training can be effective, but it has several limitations, such as increased training time and potential overfitting.

Can you explain why it might lead to overfitting?

Sure! Overfitting occurs when the model learns to perform well on the adversarial examples but fails to generalize to real-world data.

Are there any specific scenarios where adversarial training is less effective?

Yes, adversarial training may be less effective in highly dynamic environments where adversarial examples can change rapidly.

What are some alternatives to adversarial training?

Alternatives include defensive distillation, input preprocessing, and using robust optimization techniques.