A Tutorial on the Expectation-Maximization Algorithm Including Maximum-Likelihood Estimation and EM Training of Probabilistic Context-Free Grammars
<|reference_start|>A Tutorial on the Expectation-Maximization Algorithm Including Maximum-Likelihood Estimation and EM Training of Probabilistic Context-Free Grammars: The paper gives a brief review of the expectation-maximization algorithm (Dempster 1977) in the comprehensible framework of discrete mathematics. In Section 2, two prominent estimation methods, the relative-frequency estimation and the maximum-likelihood estimation are presented. Section 3 is dedicated to the expectation-maximization algorithm and a simpler variant, the generalized expectation-maximization algorithm. In Section 4, two loaded dice are rolled. A more interesting example is presented in Section 5: The estimation of probabilistic context-free grammars.<|reference_end|>
@article{prescher2004a,
    title={A Tutorial on the Expectation-Maximization Algorithm Including
  Maximum-Likelihood Estimation and EM Training of Probabilistic Context-Free
  Grammars},
    author={Detlef Prescher},
    journal={arXiv preprint arXiv:cs/0412015},
    year={2004},
    archivePrefix={arXiv},
    eprint={cs/0412015},
    primaryClass={cs.CL}
}