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Hierarchical Bayesian Models of Language and Text by Prof. Yee Whye Teh
/*Time and Date*/
3:30:00 PM on 8/31/2010
/*Location*/
SSL 150
/*Details*/
Host: Prof. Fei Sha
Speaker: Prof. Yee Whye Teh
Abstract:
In this talk I will present a new approach to modelling sequence data called the sequence memoizer. As opposed to most other sequence models, our model does not make any Markovian assumptions. Instead, we use a hierarchical Bayesian approach which enforces sharing of statistical strength across the different parts of the model. To make computations with the model efficient, and to better model the power-law statistics often observe...read more at event URL-
http://www.cs.usc.edu/calendar/csevent.asp?Event_ID=1102
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