Some advances in transformation-based part of speech tagging
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Linear hinge loss and average margin
Proceedings of the 1998 conference on Advances in neural information processing systems II
Linear concepts and hidden variables
Machine Learning
Relational Learning for NLP using Linear Threshold Elements
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Slot Grammar: A System for Simpler Construction of Practical Natural Language Grammars
Proceedings of the International Symposium on Natural Language and Logic
Introduction to the CoNLL-2000 shared task: chunking
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Use of support vector learning for chunk identification
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
The Journal of Machine Learning Research
Shallow parsing using specialized hmms
The Journal of Machine Learning Research
Text chunking based on a generalization of winnow
The Journal of Machine Learning Research
Text chunking by combining hand-crafted rules and memory-based learning
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A SNoW based supertagger with application to NP chunking
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Two-phase learning for biological event extraction and verification
ACM Transactions on Asian Language Information Processing (TALIP)
A robust multilingual portable phrase chunking system
Expert Systems with Applications: An International Journal
Efficient text chunking using linear kernel with masked method
Knowledge-Based Systems
A fast boosting-based learner for feature-rich tagging and chunking
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Combining labeled and unlabeled data with word-class distribution learning
Proceedings of the 18th ACM conference on Information and knowledge management
A classifier-based parser with linear run-time complexity
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Coping with Distribution Change in the Same Domain Using Similarity-Based Instance Weighting
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
On the role of lexical features in sequence labeling
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Hedge detection and scope finding by sequence labeling with normalized feature selection
CoNLL '10: Shared Task Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
Using suffix arrays for efficiently recognition of named entities in large scale
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
A systematic comparison of feature-rich probabilistic classifiers for NER tasks
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
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Many machine learning methods have recently been applied to natural language processing tasks. Among them, the Winnow algorithm has been argued to be particularly suitable for NLP problems, due to its robustness to irrelevant features. However in theory, Winnow may not converge for non-separable data. To remedy this problem, a modification called regularized Winnow has been proposed. In this paper, we apply this new method to text chunking. We show that this method achieves state of the art performance with significantly less computation than previous approaches.