EM Algorithm

• Widely used approach for learning in the presence of unobserved variables.
• Can be used for variables which are never directly observed, provided the general form of the probability distribution is known (unlike Gradient ascent).
• EM algorithm used widely in BBN and clustering algorithms, and Partially Observable Markov Models.
• easiest to describe EM from an example