Proving that EM improves the log probability of the training data
		• There are many ways to prove that EM improves the model. • We will prove it by showing that there is a single function that is improved by both the E-step and the M-step. – This leads to efficient “variational” methods for fitting models that are too complicated to allow an exact E-step. – Brendan Frey will show how variational model-fitting can be used for some tough vision problems.