Question 15
Consider the following statements related to optimization in deep learning. Select all statements that are correct.
Step decay, exponential decay, and cosine decay are examples of learning rate scheduling techniques.
Accelerated gradient methods necessarily require the learning rate to decrease over time in order to converge.
Momentum-based methods can improve convergence speed even when the learning rate is kept constant.
Learning rate scheduling methods introduce memory of past gradients into the optimization process.
Learning rate scheduling and accelerated gradient methods can be used together.