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Computational Linguistics and Information Processing
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= Fall 2010 =
== Fall 2013 ==  


== Computational Linguistics I (Daume) ==
* Computational Linguistics I (Boyd-Graber)
Fundamental methods in natural
language processing. Topics include: finite-state methods, context-free and extended context-free models
of syntax; parsing and semantic interpretation; n-gram and Hidden Markov models, part-of-speech
tagging; natural language applications such as machine translation, automatic summarization, and
question answering.


== Seminar in Computational Linguistics (Resnik) ==
== Spring 2013 ==
This advanced seminar will focus on computational modeling of language, including cognitive/linguistic
aspects as well as practical language technology. Bayesian and information theoretic approaches will
figure prominently. The seminar will combine reviewing fundamental material, taking a reading-group
approach to key advanced papers, and (hopefully) bringing in guest speakers. Cross-disciplinary
participation is strongly encouraged.  ([http://umiacs.umd.edu/~resnik/ling848_fa2010/ Course Web page])


== Machine Learning (Getoor) ==
* Bayesian Nonparametrics (Boyd-Graber, Daume, Feldman)
Reviews and analyzes both traditional
* Computational Linguistics II (Resnik)
symbol-processing methods and genetic algorithms as approaches to machine learning. (Neural network
* Digging into Data (Boyd-Graber)
learning methods are primarily covered in CMSC 727.) Topics include induction of decision trees and
* Machine Learning (Daume)
rules, version spaces, candidate elimination algorithm, exemplar-based learning, genetic algorithms,
evolution under artificial selection of problem-solving algorithms, system assessment, comparative
studies, and related topics.


= Spring 2010 =
== Fall 2012 ==


== Computational Linguistics II (Resnik) ==
* Computational Linguistics I (Daume)


This is the second semester in our graduate sequence in computational linguistics. Students are assumed to have taken the first semester (Ling723/CMSC723) or equivalent, and this class will provide foundations for advanced seminars in computational linguistics. Students are expected to be able to know how to program, and will exercise this ability periodically in homework assignments and/or projects.  The topics we'll cover are intended to get students up to speed on necessary background in order to understand and perform cutting-edge research in natural language processing, which requires a strong grounding in statistical NLP models and methods. Some of the topics are in the same areas as in Computational Linguistics I, but we will go deeper. As always, the syllabus is subject to revision; however, it will follow Manning and Schuetze's textbook relatively closely at least in early parts of the course.  ([http://www.umiacs.umd.edu/~resnik/ling773_sp2010/ Recent course Web page])
== Spring 2012 ==


== Cloud Computing (Boyd-Graber) ==
* [http://www.umiacs.umd.edu/~jbg/teaching/CMSC_773_2012/ Computational Linguistics II] (Boyd-Graber)
 
== Fall 2011 ==
 
* [http://www.umiacs.umd.edu/~hollingk/classes/CompLing1-f11.html Computational Linguistics I] (Hollingshead)
 
== Spring 2011 ==
 
* Computational Linguistics II (Resnik)
 
== Fall 2010 ==
 
* [http://www.umiacs.umd.edu/~hal/courses/2010F_CL1/ Computational Linguistics I] (Daume)
* [http://umiacs.umd.edu/~resnik/ling848_fa2010/ Seminar in Computational Linguistics] (Resnik)
* Machine Learning (Getoor)
 
== Spring 2010 ==
 
* [http://www.umiacs.umd.edu/~resnik/ling773_sp2010/ Computational Linguistics II] (Resnik)
* [http://www.umiacs.umd.edu/~jbg/teaching/INFM_718_2011/ Cloud Computing] (Boyd-Graber)

Revision as of 14:11, 11 December 2012

Fall 2013

  • Computational Linguistics I (Boyd-Graber)

Spring 2013

  • Bayesian Nonparametrics (Boyd-Graber, Daume, Feldman)
  • Computational Linguistics II (Resnik)
  • Digging into Data (Boyd-Graber)
  • Machine Learning (Daume)

Fall 2012

  • Computational Linguistics I (Daume)

Spring 2012

Fall 2011

Spring 2011

  • Computational Linguistics II (Resnik)

Fall 2010

Spring 2010

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