Expectation Maximization Expectation Maximization is an iterative algorithm used for maximum likelihood estimation on latent variable models. Following (Neal & Hinton 1998), we present expectation-maximization as coordinate ascent on the Evidence Lower Bound. This perspective takes much of the mystery out of the algorithm and allows us to easily derive variants like Hard EM and Variational Inference.