[Colloquium] Guest Speaker Today: Dan Roth 3:00pm

[Katherine Cumming]

Guest Speaker Today at TTI-C

Monday, April 17 @ 3:00pm


Global Inference in Learning for Natural Language Processing

  Dan Roth
  Department of Computer Science
  University of Illinois at Urbana-Champaign

Natural language decisions often involve assigning values to sets
of variables where complex and expressive dependencies can
influence, or even dictate, what assignments are possible.
Dependencies may range from simple statistical correlations to
those that are constrained by deeper structural, relational and
semantic properties of the text.

I will describe research on a framework that combines learning and
inference for this problem, of inferring structured and
constrained output. The inference process of assigning globally
optimal values to mutually dependent variables is formalized as an
optimization problem and is solved as an integer linear
programming (ILP) problem. Several key issues will be discussed,
including the incorporation of both statistical and declarative
constraints and training paradigms.

The work will be described in the context of the Semantic Role
Labeling tasks, inferring a shallow semantic analysis of sentences
at the level of "who did what to whom, how, when and why".

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