Structured Prediction for Natural Language Processing

author: Noah Smith, Language Technologies Institute, Carnegie Mellon University
published: Sept. 17, 2009,   recorded: June 2009,   views: 12688


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This tutorial will discuss the use of structured prediction methods from machine learning in natural language processing. The field of NLP has, in the past two decades, come to simultaneously rely on and challenge the field of machine learning. Statistical methods now dominate NLP, and have moved the field forward substantially, opening up new possibilities for the exploitation of data in developing NLP components and applications. However, formulations of NLP problems are often simplified for computational or practical convenience, at the expense of system performance. This tutorial aims to introduce several structured prediction problems from NLP, current solutions, and challenges that lie ahead. Applications in NLP are a mainstay at ICML conferences; many ML researchers view NLP as a primary or secondary application area of interest. This tutorial will help the broader ML community understand this important application area, how progress is measured, and the trade-offs that make it a challenge.

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Comment1 sundeep, September 22, 2009 at 11:56 p.m.:

How do I download these videos onto my hard disk? I have an extremely slow network connection; so streaming will not do for me

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