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» Applying Co-Training Methods to Statistical Parsing
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ANLP
2000
111views more  ANLP 2000»
13 years 7 months ago
Bagging and Boosting a Treebank Parser
Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser ar...
John C. Henderson, Eric Brill
ECCV
2002
Springer
14 years 8 months ago
Parsing Images into Region and Curve Processes
Abstract. Natural scenes consist of a wide variety of stochastic patterns. While many patterns are represented well by statistical models in two dimensional regions as most image s...
Zhuowen Tu, Song Chun Zhu
CSL
2008
Springer
13 years 6 months ago
A stopping criterion for active learning
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...
Andreas Vlachos
EMNLP
2011
12 years 5 months ago
Training a Parser for Machine Translation Reordering
We propose a simple training regime that can improve the extrinsic performance of a parser, given only a corpus of sentences and a way to automatically evaluate the extrinsic qual...
Jason Katz-Brown, Slav Petrov, Ryan T. McDonald, F...
ACL
2006
13 years 7 months ago
Using Machine-Learning to Assign Function Labels to Parser Output for Spanish
Data-driven grammatical function tag assignment has been studied for English using the Penn-II Treebank data. In this paper we address the question of whether such methods can be ...
Grzegorz Chrupala, Josef van Genabith