Which of the following statements is/are true about the Gradient Descent Algorithm?
A) For the non-convex loss function, there is a possibility to get stuck in local minima during optimization
B) Different initializations can lead to different outcomes
C) If the step size is too small, the progress in loss function optimization will also be very slow
D) Step size does not affect the Gradient Descent Algorithm
Answer choices
Select only one option
Only A and B
Only C and D
Only A, B, and C
A, B, C, and D