Opening the paper…
Figure from the original question paper A team has a dataset that contains 100000 samples for training a feed forward neural network. Suppose they decided to use the mini-batch gradient descent algorithm to update the weights. How many times do the weights get updated after training the network for 10 epochs with a mini-batch size of 1000? Figure from the original question paper