Question: Expectation maximization (EM) is designed to find a maximum likelihood setting of the parameters of model when some of the data is missing. Does

Expectation maximization (EM) is designed to find a maximum likelihood setting of the parameters of model when some of the data is missing. Does the algorithm converge? If so, do you obtain a locally or globally optimal set of parameters?

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