3.3) Which of the following statements is/are true?

When applying momentum optimization, setting higher momentum co-efficient will

always lead to faster convergence.

Unlike in gradient descent, in momentum optimization the gradients at a step is

dependent on the previous step.

Unlike in stochastic gradient descent, in momentum optimization the path to

convergence is faster but with high variance.