Stochastic gradient descent
	• If the dataset is highly redundant, the gradient on the first half is almost identical to the gradient on the second half. – So instead of computing the full gradient, update the weights using the gradient on the first half and then get a gradient for the new weights on the second half. – The extreme version is to update the weights after each example, but balanced mini- batches are just as good and faster in matlab.