Loss minimization in parse reranking

COLING/ACL 2006 - EMNLP 2006: 2006 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2006, Pages 560-567

  Titov, Ivan ^a   Henderson, James ^b  

^a UNIVERSITY OF GENEVA   (Switzerland)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; NATURAL LANGUAGE PROCESSING SYSTEMS;

BASELINE MODELS; DISCRIMINATIVE MODELS; EXPECTED LOSS; GENERAL METHOD; LOSS MINIMIZATION; PERCEPTRON ALGORITHMS; PROBABILISTIC MODELING; PROBABILISTIC MODELS;

LEARNING SYSTEMS;

EID: 80053375454     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1610075.1610153     Document Type: Conference Paper

References (24)

1. Eugene Charniak and Mark Johnson. 2005. Coarseto-fine n-best parsing and MaxEnt discriminative reranking. In Proc. 43rd Meeting of Association for Computational Linguistics, pages 173-180, Ann Arbor, MI.
2. Michael Collins and Nigel Duffy. 2002. New ranking algorithms for parsing and tagging: Kernels over discrete structures and the voted perceptron. In Proc. 40th Meeting of Association for Computational Linguistics, pages 263-270, Philadelphia, PA.
3. Michael Collins and Terry Koo. 2005. Discriminative reranking for natural language parsing. Computational Linguistics, 31(1):25-69.
4. Michael Collins. 1999. Head-Driven Statistical Models for Natural Language Parsing. Ph.D. thesis, University of Pennsylvania, Philadelphia, PA.
5. Michael Collins. 2000. Discriminative reranking for natural language parsing. In Proc. 17th Int. Conf. on Machine Learning, pages 175-182, Stanford, CA.
6. Joshua Goodman. 1996. Parsing algorithms and methods. In Proc. 34th Meeting of the Association for Computational Linguistics, pages 177-183, Santa Cruz, CA.
7. James Henderson and Ivan Titov. 2005. Data-defined kernels for parse reranking derived from probabilistic models. In Proc. 43rd Meeting of Association for Computational Linguistics, Ann Arbor, MI.
8. James Henderson. 2003. Inducing history representations for broad coverage statistical parsing. In Proc. joint meeting of North American Chapter of the Association for Computational Linguistics and the Human Language Technology Conf., pages 103-110, Edmonton, Canada.
9. James Henderson. 2004. Discriminative training of a neural network statistical parser. In Proc. 42nd Meeting of Association for Computational Linguistics, Barcelona, Spain.
10. Liang Huang and David Chiang. 2005. Better k-best parsing. In Proc. 9th Int.Workshop on Parsing Technologies, Vancouver, Canada.
11. Tommi S. Jaakkola and David Haussler. 1998. Exploiting generative models in discriminative classifiers. Advances in Neural Information Processes Systems 11.
12. Terry Koo and Michael Collins. 2005. Hiddenvariable models for discriminative reranking. In Proc. Conf. on Empirical Methods in Natural Language Processing, Vancouver, B.C., Canada.
13. Shankar Kumar and William Byrne. 2004. Minimum bayes-risk decoding for statistical machine translation. In Proceedings of the Human Language Technology Conference and Meeting of the North American Chapter of the Association for Computational Linguistics, Boston, MA.
14. Mitchell P. Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz. 1993. Building a large annotated corpus of English: The Penn Treebank. Computational Linguistics, 19(2):313-330.
15. Alessandro Moschitti. 2004. A study on convolutional kernels for shallow semantic parsing. In Proc. 42nd Meeting of the Association for Computational Linguistics, Barcelona, Spain.
16. John C. Platt. 1999. Probabilistic outputs for support vector machines and comparision to regularized likelihood methods. In A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 61-74. MIT Press.
17. Adwait Ratnaparkhi. 1996. A maximum entropy model for part-of-speech tagging. In Proc. Conf. on Empirical Methods in Natural Language Processing, pages 133-142, Univ. of Pennsylvania, PA.
18. Libin Shen and Aravind K. Joshi. 2003. An SVM based voting algorithm with application to parse reranking. In Proc. of the 7th Conf. on Computational Natural Language Learning, pages 9-16, Edmonton, Canada.
19. Andreas Stolcke, Yochai Konig, and Mitchel Weintraub. 1997. Explicit word error minimization in n-best list rescoring. In Proc. of 5th European Conference on Speech Communication and Technology, pages 163-165, Rhodes, Greece.
20. Ben Taskar, Dan Klein, Michael Collins, Daphne Koller, and Christopher Manning. 2004. Maxmargin parsing. In Proc. Conf. on Empirical Methods in Natural Language Processing, Barcelona, Spain.
21. Ivan Titov and James Henderson. 2005. Deriving kernels from MLP probability estimators for large categorization problems. In International Joint Conference on Neural Networks, Montreal, Canada.
22. Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims, and Yasemin Altun. 2004. Support vector machine learning for interdependent and structured output spaces. In Proc. 21st Int. Conf. on Machine Learning, pages 823-830, Banff, Alberta, Canada.
23. K. Tsuda, M. Kawanabe, G. Ratsch, S. Sonnenburg, and K. Muller. 2002. A new discriminative kernel from probabilistic models. Neural Computation, 14(10):2397-2414.
24. Alexander Yeh. 2000. More accurate tests for the statistical significance of the result differences. In Proc. 17th International Conf. on Computational Linguistics, pages 947-953, Saarbruken, Germany.