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The impact of state merging on predictive accuracy in probabilistic tree automata: Dietze’s conjecture revisited
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.ORCID-id: 0000-0001-8503-0118
2023 (engelsk)Inngår i: Fundamentals of computation theory: 24th International Symposium, FCT 2023, Trier, Germany, September 18–21, 2023, Proceedings / [ed] Henning Fernau; Klaus Jansen, Springer Nature, 2023, s. 74-87Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Dietze’s conjecture concerns the problem of equipping a tree automaton M with weights to make it probabilistic, in such a way that the resulting automaton N predicts a given corpus C as accurately as possible. The conjecture states that the accuracy cannot increase if the states in M are merged with respect to an equivalence relation ∼ so that the result is a smaller automaton M∼. Put differently, merging states can never improve predictions. This is under the assumption that both M and M∼ are bottom-up deterministic and accept every tree in C. We prove that the conjecture holds, using a construction that turns any probabilistic version N∼ of M∼ into a probabilistic version N of M, such that N assigns at least as great a weight to each tree in C as N∼ does.

sted, utgiver, år, opplag, sider
Springer Nature, 2023. s. 74-87
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14292
Emneord [en]
Probability distributions, Statistical ML, Tree automata
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Identifikatorer
URN: urn:nbn:se:umu:diva-215917DOI: 10.1007/978-3-031-43587-4_6Scopus ID: 2-s2.0-85174586168ISBN: 978-3-031-43586-7 (tryckt)ISBN: 978-3-031-43587-4 (digital)OAI: oai:DiVA.org:umu-215917DiVA, id: diva2:1809244
Konferanse
24th International Symposium on Fundamentals of Computation Theory, FCT 2023, Trier, Germany, September 18–21, 2023
Tilgjengelig fra: 2023-11-02 Laget: 2023-11-02 Sist oppdatert: 2023-11-02bibliografisk kontrollert

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