Unsupervised Learning of Syntactic Structure

author: Christopher Manning, Computer Science Department, Stanford University
published: Oct. 31, 2007,   recorded: June 2007,   views: 634
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Probabilistic models of language. ''Everybody knows that language is variable'' - Sapir (1921).
Probabilistic models give precise descriptions of a variable, uncertain world. The choice for language isn’t a dichotomy between rules and neural networks. Probabilistic models can be used over rich linguistic representations. They support inference and learning. There’s not much evidence of a poverty of the stimulus preventing them being used.

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