Michael Collins (home)

Dissertation

• Head-Driven Statistical Models for Natural Language Parsing. PhD Dissertation, University of Pennsylvania, 1999.
• Slides from my thesis defence.

Publications

2005

• Brooke Cowan and Michael Collins.
  Morphology and Reranking for the Statistical Parsing of Spanish.
  To appear in proceedings of EMNLP 2005.
  
• Terry Koo and Michael Collins.
  Hidden-Variable Models for Discriminative Reranking.
  To appear in proceedings of EMNLP 2005.
  
• Luke S. Zettlemoyer and Michael Collins.
  Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars.
  In proceedings of UAI 2005. (Received Best Paper Award.)
  
• Michael Collins, Philipp Koehn, and Ivona Kucerova.
  Clause Restructuring for Statistical Machine Translation.
  In proceedings of ACL 2005.
  
• Michael Collins, Brian Roark, and Murat Saraclar.
  Discriminative Syntactic Language Modeling for Speech Recognition.
  In proceedings of ACL 2005.
  
• Michael Collins and Terry Koo.
  Discriminative Reranking for Natural Language Parsing. (gzipped version)
  Computational Linguistics 31(1):25-69.
  (This is a preliminary version; the final journal version may differ slightly in typesetting etc.)

2004

• Peter Bartlett, Michael Collins, Ben Taskar, and David McAllester.
  Exponentiated gradient algorithms for large-margin structured classification.
  In proceedings of NIPS 2004.
  An older version of this paper, which has proofs
• Ariadna Quattoni, Michael Collins, and Trevor Darrell.
  Conditional Random Fields for Object Recognition.
  In proceedings of NIPS 2004.
• David McAllester, Michael Collins and Fernando Pereira. 2004.
  Case-factor diagrams for structured probabilistic modeling.
  UAI 2004. (Received Best Paper Award.)
• Ben Taskar, Dan Klein, Michael Collins, Daphne Koller, and Christopher Manning.
  Max-Margin Parsing.
  EMNLP 2004. (Received Best Paper Award.)
• Michael Collins and Brian Roark.
  Incremental parsing with the Perceptron algorithm.
  ACL 2004.
• Brian Roark, Murat Saraclar, Michael Collins, and Mark Johnson.
  Discriminative language modeling with conditional random fields and the perceptron algorithm.
  ACL 2004.
• Brian Roark, Murat Saraclar, and Michael Collins.
  Corrective language modeling for large vocabulary ASR with the perceptron algorithm.
  ICASSP 2004.
• Michael Collins. 2004.
  Parameter Estimation for Statistical Parsing Models: Theory and Practice of Distribution-Free Methods.
  Book chapter in Harry Bunt, John Carroll and Giorgio Satta, editors, New Developments in Parsing Technology, Kluwer. (Revised version of the paper that appeared at IWPT 2001.)

2003

• Michael Collins. 2003.
  Head-Driven Statistical Models for Natural Language Parsing.
  In Computational Linguistics.
  (This is a preliminary version; the final journal version may differ slightly in typesetting etc.)

2003 Talks

• COLT 2003 Tutorial Slides. .ps, .pdf.

2002

• Michael Collins.
  Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms.
  EMNLP 2002. (Received Best Paper Award.)
  (This paper includes theorems and proofs which apply to the algorithms in the ACL 2002 papers.)

• Michael Collins and Nigel Duffy.
  New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron
  ACL 2002.
• Michael Collins.
  Ranking Algorithms for Named-Entity Extraction: Boosting and the Voted Perceptron.
  ACL 2002.

2002 Talks

• UAI 2002 Tutorial Slides. .ps, .pdf.
• Slides for a talk on the EMNLP 2002 paper.
• Slides for a talk on the material in the two ACL 2002 papers.

2001

• Michael Collins and Nigel Duffy.
  Convolution Kernels for Natural Language.
  NIPS 2001.
• Michael Collins, Sanjoy Dasgupta and Robert E. Schapire.
  A Generalization of Principal Component Analysis to the Exponential Family.
  NIPS 2001.
• Michael Collins.
  Parameter Estimation for Statistical Parsing Models: Theory and Practice of Distribution-Free Methods .
  Paper written to accompany invited talk at IWPT 2001.
• Michael Collins, Robert E. Schapire and Yoram Singer. 2001.
  Logistic Regression, AdaBoost and Bregman Distances.
  In Machine Learning, Special Issue on New Methods for Model Selection and Model Combination. (Journal version of COLT 2000 paper.)

2000

• Michael Collins.
  Discriminative Reranking for Natural Language Parsing.
  ICML 2000.
• Michael Collins, Robert E. Schapire and Yoram Singer.
  Logistic Regression, AdaBoost and Bregman Distances.
  COLT 2000.
• Steven Abney, Michael Collins and Amit Singhal.
  Answer Extraction.
  ANLP 2000.
• Regina Barzilay, Michael Collins, Julia Hirschberg and Steve Whittaker.
  The Rules Behind Roles: Identifying Speaker Role in Radio Broadcasts.
  AAAI 2000.

1999

• Michael Collins and Yoram Singer.
  Unsupervised Models for Named Entity Classification.
  EMNLP/VLC-99.
• Michael Collins, Jan Hajic, Lance Ramshaw and Christoph Tillmann.
  A Statistical Parser for Czech.
  ACL 99.

1995-1998

• Michael Collins and Scott Miller. 1998.
  Semantic Tagging using a Probabilistic Context Free Grammar.
  In Proceedings of the Sixth Workshop on Very Large Corpora.
• Michael Collins. 1997.
  Three Generative, Lexicalised Models for Statistical Parsing.
  Proceedings of the 35th Annual Meeting of the ACL (jointly with the 8th Conference of the EACL), Madrid.
• Michael Collins. 1996.
  A New Statistical Parser Based on Bigram Lexical Dependencies.
  Proceedings of the 34th Annual Meeting of the ACL, Santa Cruz.
• Michael Collins and James Brooks. 1995.
  Prepositional Phrase Attachment through a Backed-off Model.
  Proceedings of the Third Workshop on Very Large Corpora.

Other Papers

• Michael Collins and Nigel Duffy. 2000. Parsing with a Single Neuron: Convolution Kernels for Natural Language Problems Draft version: please do not cite or distribute.

Parsing the WSJ Penn Treebank

• Identifying head-words in the WSJ Penn treebank (code used in the ACL96/97 parsing models)
• Scoring code for the Wall Street Journal Penn treebank, written by Satoshi Sekine (New York University)
• Parser output for section 0 of the treebank

Talks

• Slides for my talk at ACL/EACL97

Other Papers

• I wrote a paper on the EM (Expectation Maximization) Algorithm as one of my PhD requirements. It's a review of three papers: (Dempster, Laird and Rubin 1977), (Wu 1983), and (Jamshidian and Jennrich 1993).

Some Links

• Computational Linguistics
• PennTools, Computational Linguistics Resources At Penn
• The Computational Linguistics E-Print Archive
• The Association for Computational Linguistics
• The Corpora List Archive