1 February 1994 Algebraic learning for language acquisition
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Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172523
Event: Substance Identification Technologies, 1993, Innsbruck, Austria
Abstract
This paper explores the application of new algorithms to the adaptive language acquisition model formulated by Gorin. The new methods consists of incremental approaches for the algebraic learning of statistical associations proposed by Tishby. The incremental methods are evaluated on a text-based natural language experiment, namely the inward call manager task. Performance is evaluated with respect to the alternative methods, namely the smooth mutual information method and the pseudo-inverse solution.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin R. Farrell, Kevin R. Farrell, Richard J. Mammone, Richard J. Mammone, Allen Gorin, Allen Gorin, } "Algebraic learning for language acquisition", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); doi: 10.1117/12.172523; https://doi.org/10.1117/12.172523
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