Conference and Workshop Papers

[1] Ming-Wei Chang, Dan Goldwasser, Dan Roth, and Yuancheng Tu. Unsupervised constraint driven learning for transliteration discovery. In Proc. of the Annual Meeting of the North American Association of Computational Linguistics (NAACL), 2009. To be appeared. [ bib ]
[2] Ming-Wei Chang, Lev Ratinov, Nick Rizzolo, and Dab Roth. Learning and inference with constraints. In Proceedings of the National Conference on Artificial Intelligence (AAAI), July 2008. [ bib | .pdf ]
[3] Ming-Wei Chang, Lev Ratinov, Dab Roth, and Vivek Srikumar. Importance of semantic represenation: Dataless classification. In Proceedings of the National Conference on Artificial Intelligence (AAAI), July 2008. [ bib | .pdf ]
[4] Ming-Wei Chang, Lev Ratinov, and Dan Roth. Constraints as prior knowledge. In ICML Workshop on Prior Knowledge for Text and Language Processing, pages 32-39, July 2008. [ bib | .pdf ]
[5] Ming-Wei Chang and Dan Roth. Robust feature extension algorithms. In Learning Workshop, Snowbird, April 2008. [ bib ]
[6] Ming wei Chang, Wen tau Yih, and Robert McCann. Personalized spam filtering for gray mail. In Proc. of the Conference on Email and Anti-Spam, 2008. [ bib | .pdf ]
[7] Ming wei Chang, Wen tau Yih, and Christopher Meek. Partitioned logistic regression for spam filtering. In Proc. of the annual ACM SIGKDD conference, 2008. [ bib | .pdf ]
[8] Ming-Wei Chang, Lev Ratinov, and Dan Roth. Guiding semi-supervision with constraint-driven learning. In Proc. of the Annual Meeting of the ACL, pages 280-287, Prague, Czech Republic, June 2007. Association for Computational Linguistics. [ bib | .pdf ]
[9] Ming-Wei Chang, Quang Do, and Dan Roth. A pipeline framework for dependency parsing. In Proc. of the Annual Meeting of the ACL, pages 65-72, Sydney, Australia, July 2006. Association for Computational Linguistics. [ bib | www: ]
[10] Ming-Wei Chang, Quang Do, and Dan Roth. A pipeline model for bottom-up dependency parsing. In Proc. of the Annual Conference on Computational Natural Language Learning (CoNLL), pages 186-190, New York City, June 2006. Association for Computational Linguistics. [ bib | .pdf ]
[11] Ming-Wei Chang, Bo-Juen Chen, and Chih-Jen Lin. EUNITE network competition: Electricity load forecasting, 2002. Winner of EUNITE world wide competition on electricity load prediction. [ bib | .ps.gz ]
[12] Ming-Wei Chang, Chih-Jen Lin, and Ruby C. Weng. Analysis of switching dynamics with competing support vector machines. In Proceedings of IJCNN, pages 2387-2392, 2002. [ bib | .pdf ]
[13] Ming-Wei Chang, Chih-Jen Lin, and Ruby C. Weng. Analysis of nonstationary time series using support vector machines. In Seong-Whan Lee and Alessandro Verri, editors, Proceedings of SVM 2002, Lecture Notes in Computer Science 2388, pages 160-170, New York, NY, USA, 2002. Springer-Verlag Inc. [ bib | .ps.gz ]
[14] Ming-Wei Chang, Chih-Jen Lin, and Ruby C. Weng. Adaptive deterministic annealing for two applications: competing SVR of switching dynamics and travelling salesman problems. In Proceedings of ICONIP 2002, pages 920-924, 2002. [ bib | .pdf ]

Journal Papers

[1] Ming-Wei Chang and Chih-Jen Lin. Leave-one-out bounds for support vector regression model selection. Neural Computation, 17:1188-1222, 2005. [ bib | .pdf ]
[2] Bo-Juen Chen, Ming-Wei Chang, and Chih-Jen Lin. Load forecasting using support vector machines: A study on EUNITE competition 2001. IEEE Transactions on Power Systems, 19(4):1821-1830, November 2004. [ bib | .pdf ]
[3] Ming-Wei Chang, Chih-Jen Lin, and Ruby C. Weng. Analysis of switching dynamics with competing support vector machines. IEEE Transactions on Neural Networks, 15(3):720-727, 2004. [ bib | .pdf ]
shorter version appeared in IJCNN 2002.

Book Chapters

[1] Ming-Wei Chang, Quang Do, and Dan Roth. Multilingual dependency parsing: A pipeline approach. In Nicolas Nicolov, editor, Recent Advances in Natural Language Processing, pages 195-204. Springer-Verlag, July 2006. [ bib | .pdf ]
Analysis of a pipeline model with applications to dependency parsing. Combines ACL'06 and CoNLL'06

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