running decent that one is simpler to analyze but it's also less interesting because it minimizes directly the population loss and there is no notion of the generalization gap the training test are the same so a lot of the mysteries about how comes the train error can be so much smaller than the test error that we are kind of asking and deep learning cannot really be answered by looking at the online stochastic gravity scene it's also not used in practice what's used in practice is multipass stochastic gradient descent