Automatic Derivation of Statistical Algorithms: The EM Family and Beyond

Fischer, Bernd, Schumann, Johann, Buntine, Wray, Gray, Alexander G.

Neural Information Processing Systems 

Machine learning has reached a point where many probabilistic methods can be understood as variations, extensions and combinations of a much smaller set of abstract themes, e.g., as different instances of the EM algorithm. This enables the systematic derivation of algorithms customized for different models.

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