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[nl-uiuc] FW: [dssifac] DSSI Speaker: James Clarke

From: "Roth, Dan" <danr AT uiuc.edu>
To: "nl-uiuc AT cs.uiuc.edu" <nl-uiuc AT cs.uiuc.edu>, "aivr AT cs.uiuc.edu" <aivr AT cs.uiuc.edu>, "dais AT cs.uiuc.edu" <dais AT cs.uiuc.edu>, "cogcomp AT cs.uiuc.edu" <cogcomp AT cs.uiuc.edu>, "vision AT cs.uiuc.edu" <vision AT cs.uiuc.edu>, "krr-group AT cs.uiuc.edu" <krr-group AT cs.uiuc.edu>, "group AT vision.ai.uiuc.edu" <group AT vision2.ai.uiuc.edu>
Cc: cinda heeren <heeren AT cs.uiuc.edu>
Subject: [nl-uiuc] FW: [dssifac] DSSI Speaker: James Clarke
Date: Thu, 26 Jun 2008 11:11:22 -0500
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From: dssifac-bounces AT cs.uiuc.edu [mailto:dssifac-bounces AT cs.uiuc.edu] On Behalf Of cinda heeren
Sent: Thursday, June 26, 2008 11:01 AM
To: lvantang AT usc.edu; ruiyangwu AT gmail.com; Sharon M. Paradesi; yliu49 AT emory.edu; jxiao AT cs.utsa.edu; cloverzj AT ksu.edu; Tim Weninger; xiajing AT ksu.edu; welshamy AT ksu.edu; Ashish Panday; kjaeyeon AT iit.edu; nathanielryckman AT yahoo.com; zhourui AT ksu.edu; caitlinl AT ksu.edu; sahenke AT gmail.com; shydslow AT aol.com; jen_nsims AT yahoo.com; belljessicaf_05 AT yahoo.com; smartypantsizit AT yahoo.com; Donee' McAllister; William H. Hsu; Loeb, Alexander Thomas; Tim Vieira; Muriello, Daniel G; Robinson, Jacob C; Paul, Michael J; James Clarke; dssifac AT cs.uiuc.edu; Sammons, Mark
Subject: [dssifac] DSSI Speaker: James Clarke

Hi Everyone! It looks like we're continuing our pattern of Friday talks... (DSSI students, please plan to attend!) There will be a lunch following the talk in the usual spot (outside 2405 siebel).

Who: James Clarke, http://homepages.inf.ed.ac.uk/s0460084

When: 10:30a, Friday, 6/27

Where: Siebel 3405

What: Integer Linear Programming for NLP

Abstract:

Many natural language processing tasks, such as machine translation, parsing and generation; require a decoding algorithm to find the best solution for a given input and model. The decoding problem is also referred to as the inference or search problem. Ideally during decoding we should find the optimal solution in an efficient manner. However, many decoding algorithms find sub-optimal solutions or force us to make strong assumptions of conditional independence between variables. Formulating decoding as an integer linear program allows us to infer globally optimal solutions and enforce global constraints.

In this talk we give an introduction to the concepts, formulation and solving of integer linear programs. We demonstrate how integer linear programming can be used for decoding in two applications: sentence compression and dependency parsing. Our approach can yield state-of-the-art or better performance by introducing linguistically motivated constraints that allow us to model the global properties observed in language.

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[nl-uiuc] FW: [dssifac] DSSI Speaker: James Clarke, Roth, Dan, 06/26/2008