Spring 2017

Continuous State Machines and Grammars for Linguistic Structure Prediction

Wednesday, Mar. 29, 2017 9:30 am10:10 am PDT

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Linguistic structure prediction infers abstract representations of text, like syntax trees and semantic graphs, enabling interpretation in applications like question answering, information extraction, and opinion analysis.  This talk is about the latest family of methods for linguistic structure prediction, which make heavy use of representation learning via neural networks.  I'll present these new methods as continuous generalizations of state machines and probabilistic grammars.  I'll show how they've led to fast and accurate performance on several syntactic and semantic parsing problems.