Dan Garrette
Ph.D. Student
Dan's research focuses on Natural Language Processing and Machine Learning.
A Formal Approach to Linking Logical Form and Vector-Space Lexical Semantics 2013
Dan Garrette, Katrin Erk, Raymond J. Mooney, In Computing Meaning, Harry Bunt, Johan Bos, and Stephen Pulman (Eds.), Vol. 4, pp. 27--48, Berlin 2013. Springer.
Learning a Part-of-Speech Tagger from Two Hours of Annotation 2013
Dan Garrette, Jason Baldridge , Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT-13) (2013), pp. 138--147.
Montague Meets Markov: Deep Semantics with Probabilistic Logical Form 2013
Islam Beltagy, Cuong Chau, Gemma Boleda, Dan Garrette, Katrin Erk, Raymond Mooney, Proceedings of the Second Joint Conference on Lexical and Computational Semantics (*Sem-2013) (2013), pp. 11--21.
Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages 2013
Dan Garrette, Jason Mielens, and Jason Baldridge , To Appear Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013) (2013), pp. 583--592.
Type-Supervised Hidden Markov Models for Part-of-Speech Tagging with Incomplete Tag Dictionaries 2012
Dan Garrette and Jason Baldridge, In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2012), pp. 821--831, Jeju, Korea, July 2012.
Integrating Logical Representations with Probabilistic Information using Markov Logic 2011
Dan Garrette, Katrin Erk, Raymond Mooney, In Proceedings of the International Conference on Computational Semantics, pp. 105--114, Oxford, England, January 2011.
Currently affiliated with Machine Learning