CS 6741

Last Updated

  • Schedule of Classes - January 19, 2016 6:14PM EST
  • Course Catalog - January 19, 2016 6:21PM EST

CS 6741
Structured Prediction for Natural Language Processing

Course information provided by the 2015-2016 Catalog.

Robust language understanding has the potential to transform how we interact with computers, extract information from text and study language on large scale. However, to accurately recover the meaning of language, automated systems must learn to reason about the meaning of words and the intricate structures they combine to. This research-oriented course examines machine learning and inference methods for recovering structured representations of language meaning. Possible topics include formalisms, inference and learning for: sequence models (tagging, named-entity recognition), tree models (constituency and dependency parsing), mapping sentences to logical form representations and alignment models (machine translation).


Prerequisites/Corequisites Prerequisites: CS 2110 or equivalent programming experience, a course in machine learning (CS 4780/CS 5780, CS 6780 or equivalent).

Permission Note Enrollment limited to Ph.D. students.

When Offered Fall.

View Enrollment Information

Syllabi: none

  •   Regular Academic Session.  Combined with: CS 6741

  • 3 Credits Graded

  • 18766 CS 6741   LEC 001

  •  

  • Instruction Mode: Distance Learning - WWW

    Enrollment limited to PhD students in Ithaca - offered via distance learning.

Syllabi: none

  •   Regular Academic Session.  Combined with: CS 6741

  • 3 Credits Graded

  • 18765 CS 6741   LEC 030

  •  

  • Instruction Mode: In Person

    Enrollment limited to PhD students at Cornell Tech - offered in NYC.