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SUMMARY:Learning Language\, Evolving Languages - Ted Briscoe\, Computer La
 boratory\, University of Cambridge
DTSTART:20140515T150000Z
DTEND:20140515T163000Z
UID:TALK52412@talks.cam.ac.uk
CONTACT:Theodora Alexopoulou
DESCRIPTION:I will introduce the Bayesian approach to grammar induction wi
 thin an evolutionary and cognitive framework for thinking about language a
 cquisition by first describing a simple though linguistically-inadequate a
 ccount of the acquisition of a limitedclass of probabalistic context-free 
 grammars. I will then introduce a Bayesian Incremental Parameter Setting (
 BIPS) algorithm for learning Generalized Categorial Grammars (GCG)\, which
  Iwill argue is cognitively feasible\, linguistically-adequate\, and offer
 s plausible explanations for some putative exceptionless and\nstatistical 
 (typological) linguistic universals when embedded in an\nevolutionary mode
 l of language development and change.\n\nSurprisingly\, the BIPS-GCG theor
 y is most naturally treated as a\nnon-parametric Bayesian process\, in whi
 ch `hidden' variables can be\nestimated deterministically (unlike\, say\, 
 in Latent Dirichlet Processes)\, though the resulting theory bears similar
 ities to recent accounts of parameter setting emerging from the ReCoS proj
 ect at DTAL.\n\nThis talk is presented by the Cambridge Linguistics Forum.
LOCATION:LG19\, Law Faculty\, Sidgwick site
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