Choose all of the True statements regarding SGD. O Using a small learning rate could cause the optimizer to converge more slowly. O While optimizing a convex function using SGD, it is guaranteed that given enough time, the optimizer will always converge to the global minimum regardless of the learning rate. O 1. Using the following sequence of learning rate will always result in converging to a local minimum. a = 1/t +1 O The main idea behind SGD is that each step is always in the right direction when doing the approximation.
