I am having problems finding a well thought out complete explanation of expectation maximization. Does anyone have a best source for someone completely new to this stuff?
Expectation Maximization algorithm
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0It is most likely an initialization issue. E.g. if you are training a Gaussian mixture model and all mixture parameters are initialized to the same values (e.g. all means are the same), then you will end up with trivial solutions. Try randomizing the initial parameters. – 2012-08-30
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Check out the following tutorials:
T. K. Moon, "The expectation-maximization algorithm", IEEE Signal Processing Magazine, vol. 13, no. 6, pp. 47-60, 1996.
J. A. Bilmes, "A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models".
Of course, you can refer to the original paper by Dempster et al. But it might be slightly hard for a first read.
Another reference is the Pattern Recognition and Machine Learning book by C. Bishop. It has a nice (and intuitive) explanation for EM.