What are some robust methods in AI?

What are some robust methods in AI?

Robust methods in AI include techniques like ensemble learning, regularization, and adversarial training. Would you like to know more about any specific method?

Can you explain ensemble learning?

Ensemble learning combines multiple models to improve performance. Techniques like bagging and boosting are common examples.

What is regularization and why is it important?

Regularization is a technique used to prevent overfitting by adding a penalty to the loss function. It's crucial for improving model generalization.

How does adversarial training work?

Adversarial training involves training models on adversarial examples to enhance their robustness against attacks. It helps improve security.

What are some applications of these methods?

These methods are widely used in image recognition, natural language processing, and fraud detection, among other fields.