Paper: Text Chunking Using Regularized Winnow

ACL ID P01-1069
Title Text Chunking Using Regularized Winnow
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2001

Many machine learning methods have recently been applied to natural lan- guage processing tasks. Among them, the Winnow algorithm has been ar- gued to be particularly suitable for NLP problems, due to its robustness to ir- relevant features. However in theory, Winnow may not converge for non- separable data. To remedy this prob- lem, a modification called regularized Winnow has been proposed. In this pa- per, 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.