@InProceedings{Prescher:2001_2,
AUTHOR = {Prescher, Detlef},
TITLE = {InsideOutside Estimation Meets Dynamic EM},
YEAR = {2001},
BOOKTITLE = {Proceedings of the 7th International Workshop on Parsing Technologies (IWPT01), October 1719},
PAGES = {241244},
ADDRESS = {Beijing, China},
URL = {http://www.dfki.de/~prescher/papers/bib/2001iwpt.prescher.pdf},
ABSTRACT = {It is an interesting fact that most of the stochastic models used by linguists can be interpreted as probabilistic contextfree grammars. In this paper, this result will be accompanied by the formal proof that the insideoutside algorithm, the standard training method for probabilistic contextfree grammars, can be regarded as a dynamicprogramming variant of the EM algorithm. Even if this result is considered in isolation this means that most of the probabilistic models used by linguists are trained by a version of the EM algorithm. However, this result is even more interesting when considered in a theoretical context because the wellknown convergence behavior of the insideoutside algorithm has been confirmed by many experiments but it seems that it never has been formally proved. Furthermore, being a version of the EM algorithm, the insideoutside algorithm also inherits the good convergence behavior of EM. We therefore contend that the as yet imperfect line of argumentation can be transformed into a coherent proof.},
ANNOTE = {COLIURL : Prescher:2001:IOEb.pdf} }
