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Sequence Encoders Enable Large-Scale Lexical Modeling: Reply to Bowers and Davis (2009)

Sibley, Kello, Plaut, and Elman (2008) proposed the sequence encoder as a model that learns fixed-width distributed representations of variable-length sequences. In doing so, the sequence encoder overcomes problems that have restricted models of word reading and recognition to processing only monosy...

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Библиографические подробности
Главные авторы: Sibley, Daragh E., Kello, Christopher T., Plaut, David C., Elman, Jeffrey L.
Формат: Artigo
Язык:Inglês
Опубликовано: 2009
Предметы:
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC2746651/
https://ncbi.nlm.nih.gov/pubmed/20046958
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/j.1551-6709.2009.01064.x
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