What is the difference between fixed and adaptive learning rates in machine learning?

What is the difference between fixed and adaptive learning rates in machine learning?

Fixed learning rates remain constant throughout training, while adaptive learning rates adjust based on training progress.

Can you give me an example of when to use each type?

Use a fixed learning rate for simpler problems, and adaptive rates for complex tasks where the learning process varies.

What are the advantages of using an adaptive learning rate?

Adaptive learning rates can lead to faster convergence and better performance by adjusting to the landscape of the loss function.

Are there any downsides to using adaptive learning rates?

Yes, they can sometimes lead to overshooting the minimum or getting stuck in local minima if not tuned properly.