What are the common challenges in adversarial training?

What are the common challenges in adversarial training?

Adversarial training faces several challenges, including data scarcity, computational cost, and model robustness.

Can you elaborate on the issue of data scarcity?

Data scarcity in adversarial training refers to the limited availability of labeled adversarial examples, making it hard to train models effectively.

What about the computational costs?

Computational costs can be high due to the need for generating adversarial examples and training models on these complex datasets.

How does model robustness play a role?

Model robustness is crucial as it determines how well a model can withstand adversarial attacks, which is often a challenge to achieve.