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Report (Bericht) zugänglich unter
URN: urn:nbn:de:bsz:291-scidok-50019
URL: http://scidok.sulb.uni-saarland.de/volltexte/2012/5001/


Inside-outside estimation meets dynamic EM : gold

Prescher, Detlef

Quelle: (2001) Kaiserslautern ; Saarbrücken : DFKI, 2001
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Dokument 1.pdf (2.662 KB)

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SWD-Schlagwörter: Künstliche Intelligenz
Institut: DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
DDC-Sachgruppe: Informatik
Dokumentart: Report (Bericht)
Schriftenreihe: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Bandnummer: 01-02
Sprache: Englisch
Erstellungsjahr: 2001
Publikationsdatum: 05.12.2012
Kurzfassung auf Englisch: It is an interesting fact that most of the stochastic models used by linguists can be interpreted as probabilistic context-free grammars (Prescher 2001). In this paper, this result will be accompanied by the formal proof that the inside-outside algorithm, the standard training method for probabilistic context-free grammars, can be regarded as dynamic-programming 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 well-known convergence behavior of the inside-outside 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 inside-outside algorithm also inherits the good convergence behavior of EM. We therefore contend that the yet imperfect line of argumentation can be transformed into a coherent proof.
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