The ‘trainAutoencoder’ function uses optimization algorithms that don't expose a learning rate parameter in the same way that gradient descent-based algorithms do. It typically uses variations of conjugate gradient backpropagation, which automatically adjust their search step size based on the gradient information. These algorithms focus on efficiently finding a minimum of the loss function without requiring manual tuning of a learning rate.
For more information, you can refer to the documentation link below:
