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It includes a graphical example to provide some intuition.
1 Intuitive Explanation of EM
EM is an iterative optimization method to estimate some unknown parameters, given
measurement data U. However, we are not given some “hidden” nuisance variables J,
which need to be integrated out. In particular, we want to maximize the posterior
probability of the parameters given the data U, marginalizing over J:
= argmax
X
J2Jn
P(; JjU) (1)
The intuition behind EM is an old one: alternate between estimating the unknowns
and the hidden variables J. This idea has been around for a long time...
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