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Computational Linguistics and Information Processing

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== 09/12/2012: 5 Minute Madness (Part II) ==
== 09/12/2012: 5 Minute Madness (Part II) ==


== 09/19/2012: Earl Wagner ==
== 09/19/2012: CoB: Pairwise Similarity on Large Text Collections with MapReduce==
'''Speaker:''' Earl Wagner, University of Maryland<br/>
'''Time:''' Wednesday, September 26, 2012, 11:00 AM<br/>
'''Venue:''' AVW 3258<br/>
 
== 09/26/2012: Hal Daume III ==


== 10/03/2012: Shay Cohen ==
== 10/03/2012: Shay Cohen ==

Revision as of 12:23, 1 September 2012

The CLIP Colloquium is a weekly speaker series organized and hosted by CLIP Lab. The talks are open to everyone. Most talks are held at 11AM in AV Williams 3258 unless otherwise noted. Typically, external speakers have slots for one-on-one meetings with Maryland researchers before and after the talks; contact the host if you'd like to have a meeting.

If you would like to get on the cl-colloquium@umiacs.umd.edu list or for other questions about the colloquium series, e-mail Jimmy Lin, the current organizer.


{{#widget:Google Calendar |id=lqah25nfftkqi2msv25trab8pk@group.calendar.google.com |color=B1440E |title=Upcoming Talks |view=AGENDA |height=300 }}

09/05/2012: 5 Minute Madness (Part I)

09/12/2012: 5 Minute Madness (Part II)

09/19/2012: CoB: Pairwise Similarity on Large Text Collections with MapReduce

Speaker: Earl Wagner, University of Maryland
Time: Wednesday, September 26, 2012, 11:00 AM
Venue: AVW 3258

09/26/2012: Hal Daume III

10/03/2012: Shay Cohen

10/10/2012: Beyond MaltParser - Advances in Transition-Based Dependency Parsing

Speaker: Joakim Nivre, Uppsala University / Google
Time: Wednesday, October 10, 2012, 11:00 AM
Venue: AVW 3258

Abstract: The transition-based approach to dependency parsing has become popular thanks to its simplicity and efficiency. Systems like MaltParser achieve linear-time parsing with projective dependency trees using locally trained classifiers to predict the next parsing action and greedy best-first search to retrieve the optimal parse tree, assuming that the input sentence has been morphologically disambiguated using a part-of-speech tagger. In this talk, I survey recent developments in transition-based dependency parsing that address some of the limitations of the basic transition-based approach. First, I show how globally trained classifiers and beam search can be used to mitigate error propagation and enable richer feature representations. Secondly, I discuss different methods for extending the coverage to non-projective trees, which are required for linguistic adequacy in many languages.Finally, I present a model for joint tagging and parsing that leads to improvements in both tagging and parsing accuracy as compared to the standard pipeline approach.

About the Speaker: Joakim Nivre is Professor of Computational Linguistics at Uppsala University and currently visiting scientist at Google, New York. He holds a Ph.D. in General Linguistics from the University of Gothenburg and a Ph.D. in Computer Science from Växjö University. Joakim's research focuses on data-driven methods for natural language processing, in particular for syntactic and semantic analysis. He is one of the main developers of the transition-based approach to syntactic dependency parsing, described in his 2006 book Inductive Dependency Parsing and implemented in the MaltParser system. Joakim's current research interests include the analysis of mildly non-projective dependency structures, the integration of morphological and syntactic processing for richly inflected languages, and methods for cross-framework parser evaluation. He has produced over 150 scientific publications, including 3 books, and has given nearly 70 invited talks at conferences and institutions around the world. He is the current secretary of the European Chapter of the Association for Computational Linguistics.

Host: Hal Daume III, hal@umd.edu

10/31/2012: Kilian Weinberger

Previous Talks