Question 18
Suppose you build a neural network with one hidden layer that uses sigmoid as an activation function and an output layer with a softmax activation function. You initialize the hidden layer weights W1 randomly and set the output layer weights W2 to all zeros. Assume the bias is set to be zero. You train the network using stochastic gradient descent. Based on the above data, answer the given subquestions.
After one iteration of gradient descent, will the new weight for W1 be the same as the previous weight?
Yes
No