What distinguishes Nesterov Accelerated Gradient $($NAG$)$ from standard momentum in gradient descent?

A$)$ NAG adjusts the parameters before calculating the gradient, not after.

B$)$ NAG uses a larger fixed momentum coefficient.

C$)$ NAG calculates gradients without considering previous updates.

D$)$ NAG eliminates the need for a learning rate.