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Abstract: This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure. Important new language learning results follow directly: explicitly calculated sample complexity learning times under different input distribution assumptions (including CHILDES database language input) and learning regimes. We also briefly describe a new way to formally model (rapid) diachronic syntax change. (Update)
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BibTeX entry: (Update)
@misc{ parameter-markov,
author = "For Finite Parameter",
title = "A Markov Language Learning Model",
url = "citeseer.ist.psu.edu/586721.html" }
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