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Thesis

  • David McClosky. Any Domain Parsing: Automatic Domain Adapatation for Parsing. Ph.D. Thesis, Brown. May 2010. [PDF] [thesis defense slides]

2011

  • David McClosky, Mihai Surdeanu, and Chris Manning. Event Extraction as Dependency Parsing. Association of Computational Linguistics: Human Language Technologies (ACL 2011), Portland, Oregon. [PDF]
  • Sebastian Riedel, David McClosky, Mihai Surdeanu, Andrew McCallum, and Chris Manning. Model Combination for Event Extraction in BioNLP 2011. Natural Language Processing in Biomedicine ACL 2011 Workshop (BioNLP 2011), Portland, Oregon. [PDF]
  • David McClosky, Mihai Surdeanu, and Chris Manning. Event Extraction as Dependency Parsing in BioNLP 2011. Natural Language Processing in Biomedicine ACL 2011 Workshop (BioNLP 2011), Portland, Oregon. [PDF]
  • Mihai Surdeanu, David McClosky, Mason R. Smith, Andrey Gusev, and Christopher D. Manning. Customizing an Information Extraction System to a New Domain. Workshop on Relational Models of Semantics (RELMS 2011), Portland, Oregon. [PDF]

2010

  • David McClosky, Eugene Charniak, and Mark Johnson. Automatic Domain Adapatation for Parsing. North American Chapter of the Association for Computational Linguistics - Human Language Technologies 2010 Conference (NAACL-HLT 2010), Los Angeles, CA. [PS] [PDF] [slides]
  • Mihai Surdeanu, David McClosky, Julie Tibshirani, John Bauer, Angel X. Chang, Valentin I. Spitkovsky, and Christopher D. Manning. A Simple Distant Supervision Approach for the TAC-KBP Slot Filling Task. Third Text Analysis Conference (TAC 2010), Gaithersburg, MD. [PDF] [bib]

2009

  • William P. Headden III, Mark Johnson, and David McClosky. Improving Unsupervised Dependency Parsing with Richer Contexts and Smoothing. North American Chapter of the Association for Computational Linguistics - Human Language Technologies 2009 Conference (NAACL-HLT 2009), Boulder, Colorado. [PS] [PDF]

2008

  • David McClosky, Eugene Charniak, and Mark Johnson. BLLIP North American News Text. Linguistic Data Consortium, Philadelphia, 2008. [complete] [general]
  • David McClosky. Modeling Valence Effects in Unsupervised Grammar Induction. Technical Report CS-09-01, Brown University, Providence, RI, USA, 2008. [PS] [PDF]
  • David McClosky, Eugene Charniak, and Mark Johnson. When is Self-Training Effective for Parsing? Proceedings of the International Conference on Computational Linguistics (COLING 2008), Manchester, UK. [PS] [PDF] [slides]
  • William P. Headden III, David McClosky, and Eugene Charniak. Evaluating Unsupervised Part-of-Speech Tagging for Grammar Induction. Proceedings of the International Conference on Computational Linguistics (COLING 2008), Manchester, UK. [PS] [PDF]
  • David McClosky and Eugene Charniak. Self-Training for Biomedical Parsing. Proceedings of the Association for Computational Linguistics (ACL 2008, short papers), Columbus, Ohio. [PS] [PDF]

2006

  • David McClosky, Eugene Charniak, and Mark Johnson. Reranking and Self-Training for Parser Adaptation. Proceedings of the Association for Computational Linguistics (COLING-ACL 2006), Sydney, Australia. [PS] [PDF] [slides]
  • Matthew Lease, Eugene Charniak, Mark Johnson, and David McClosky. A Look At Parsing and Its Applications. Proceedings of American Association for Artificial Intelligence (AAAI 2006), Boston, Massachusetts. [PS] [PDF]
  • David McClosky, Eugene Charniak, and Mark Johnson. Effective Self-Training for Parsing. Proceedings of the Conference on Human Language Technology and North American chapter of the Association for Computational Linguistics (HLT-NAACL 2006), Brooklyn, New York. [PS] [PDF] [slides] [self-trained parser model]

2005

  • Sharon Goldwater and David McClosky. Improving Statistical MT through Morphological Analysis. Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (HLT-EMNLP 2005), Vancouver, Canada. [PS] [PDF] [poster]

class papers

  • David McClosky. Restricted Programming Paradigms for Parallelism for CS275 (Topics in Parallel and Distributed Computing) [PS] [PDF]