Michael Collins (home)
Dissertation
Publications
2014
Karl Stratos, Dokyum Kim, Michael Collins, and Daniel Hsu.
A Spectral Algorithm for Learning
ClassBased ngram Models of Natural Language.
In UAI 2014.
(Here is a longer
version, with an appendix on sample complexity.)

Shay B. Cohen, Karl Stratos, Michael Collins, Dean
P. Foster and Lyle Ungar.
Spectral Learning of LatentVariable PCFGs: Algorithms and Sample
Complexity.
In JMLR 2014.

Shay B. Cohen and Michael Collins.
A Provably Correct Learning
Algorithm for LatentVariable PCFGs.
In proceedings of ACL 2014.

YinWen Chang, Alexander M. Rush, Michael Collins, and John DeNero.
A Lagrangian Relaxation Algorithm for Bidirectional Word Alignment.
In proceedings of ACL 2014.

Arvind Neelakantan and Michael Collins.
Learning Dictionaries for Named Entity Recognition using Minimal Supervision.
In proceedings of EACL 2014.
2013

Andrei Simion, Michael Collins, and Clifford Stein.
A Convex Alternative to IBM Model 2.
In proceedings of EMNLP 2013.

Alexander M. Rush, YinWen Chang, and Michael Collins.
Optimal Beam Search for Machine Translation.
In proceedings of EMNLP 2013.

Karl Stratos, Alexander M. Rush, Shay B. Cohen and Michael Collins.
Spectral Learning of Refinement HMMs.
In proceedings of CoNLL 2013.

Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, and Lyle Ungar.
Experiments with Spectral Learning of LatentVariable PCFGs.
In proceedings of NAACL 2013.

Shay B. Cohen, Giorgio Satta, and Michael Collins.
Approximate PCFG Parsing Using Tensor Decomposition.
In proceedings of NAACL 2013.
2012

Shay B. Cohen and Michael Collins.
Tensor Decomposition for Fast Parsing with LatentVariable PCFGs.
In proceedings of NIPS 2012.

Shay B. Cohen, Karl Stratos, Michael Collins, Dean P. Foster, and Lyle Ungar.
Spectral Learning of LatentVariable PCFGs.
In proceedings of ACL 2012.
Here is a longer version
of the paper, which includes proofs and should be more readable
(less compressed, cleaner notation) than the ACL paper.

Alexander M. Rush and Michael Collins.
A tutorial on Lagrangian
relaxation and dual decomposition for NLP.
In
Journal of Artificial Intelligence Research.

Alexander M. Rush, Roi Reichart, Michael Collins and Amir Globerson.
Improved Parsing and POS Tagging Using InterSentence Consistency Constraints.
To appear in proceedings of EMNLP 2012.

Paramveer Dhillon, Jordan Rodu, Michael Collins, Dean P. Foster and Lyle Ungar.
Spectral Dependency Parsing with Latent Variables.
To appear in proceedings of EMNLP 2012.
2011
2010

Terry Koo, Alexander M. Rush, Michael Collins, Tommi Jaakkola, and David
Sontag.
Dual Decomposition for Parsing with NonProjective Head Automata.
In proceedings of EMNLP 2010.
(Received Best Paper Award.)

Alexander M. Rush, David Sontag, Michael Collins, and Tommi Jaakkola.
On Dual Decomposition and Linear Programming Relaxations for Natural
Language Processing.
In proceedings of EMNLP 2010.

Terry Koo and Michael Collins.
Efficient Thirdorder Dependency Parsers.
In proceedings of ACL 2010.

Fadi Biadsy, Julia Hirschberg, and Michael Collins.
Dialect Recognition Using a PhoneGMMSupervectorBased SVM Kernel.
To appear in proceedings of Interspeech 2010.

Shivani Agarwal and Michael Collins.
Maximum Margin Ranking Algorithms for Information Retrieval.
In Proceedings of the 32nd European Conference on Information Retrieval
(ECIR), 2010.
2009
2008

Ariadna Quattoni, Michael Collins, and Trevor Darrell.
Transfer Learning for Image Classification with Sparse
Prototype Representations.
In
Proceedings of CVPR 2008.

Xavier Carreras, Michael Collins, and Terry Koo.
TAG, Dynamic Programming and the Perceptron for
Efficient, Featurerich Parsing.
In
Proceedings of CONLL 2008.
(Received Best Paper Award.)
Video
of an invited talk at ICML 2008,
mainly focusing on work described in the CONLL 2008 paper.

Terry Koo, Xavier Carreras, and Michael Collins.
Simple Semisupervised Dependency Parsing.
In
Proceedings of ACL 2008.

Michael Collins, Amir Globerson, Terry Koo, Xavier Carreras, and
Peter Bartlett.
Exponentiated Gradient Algorithms for Conditional
Random Fields and MaxMargin Markov Networks.
To appear in JMLR (the paper linked here is the submission version,
the final version will be posted shortly).
This paper extends the ICML 2007 and NIPS 2004 papers on EG
algorithms with additional proofs and experiments.
2007

Natasha SinghMiller, Michael Collins, and Timothy J. Hazen. 2007.
Dimensionality Reduction for Speech
Recognition using Neighborhood Components Analysis.
In
Proceedings of Interspeech 2007 (ICSLP 2007).
 Amir Globerson, Terry Koo, Xavier Carreras, and Michael Collins.
2007.
Exponentiated Gradient Algorithms for LogLinear Structured Prediction.
In proceedings of ICML 2007.
See the JMLR 2008 paper listed above for new work on this topic.

Terry Koo, Amir Globerson, Xavier Carreras, and Michael Collins. 2007.
Structured Prediction Models via the MatrixTree Theorem.
In proceedings of EMNLPCoNLL 2007.

Chao Wang, Michael Collins, and Philipp Koehn. 2007.
Chinese Syntactic Reordering for Statistical Machine Translation.
In proceedings of EMNLPCoNLL 2007.

Luke Zettlemoyer and Michael Collins. 2007.
Online Learning of Relaxed CCG Grammars for Parsing to Logical Form.
In proceedings of EMNLPCoNLL 2007.
 Ariadna Quattoni, Michael Collins, and Trevor Darrell.
2007.
Learning Visual Representations using Images with Captions.
In proceedings of CVPR 2007.

Natasha SinghMiller and Michael Collins. 2007.
Triggerbased Language Modeling using a Losssensitive Perceptron Algorithm.
In proceedings of ICASSP 2007.
 Brian Roark, Murat Saraclar, and Michael Collins. 2007.
Discriminative ngram language modeling.
Computer Speech and Language, 21(2):373392.
(Follow
this link for
a preliminary version; the final journal version
may differ slightly in typesetting etc.)
 Ariadna Quattoni, Sybor Wang, LouisPhilippe Morency, Michael
Collins, and Trevor Darrell. 2007.
Hidden Conditional Random Fields.
To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence.
2006
2005
2004

Peter Bartlett, Michael Collins, Ben Taskar, and David McAllester.
Exponentiated gradient algorithms
for largemargin structured classification.
In proceedings of NIPS 2004.
An older version of this paper, which has proofs
Slides from a talk given at CONLL 2006

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.
Casefactor diagrams for structured probabilistic modeling.
UAI 2004.
(Received Best Paper Award.)

Ben Taskar, Dan Klein, Michael Collins, Daphne Koller, and
Christopher Manning.
MaxMargin 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 DistributionFree 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
2003 Talks
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
2000
1999
19951998
Other Papers
Parsing the WSJ Penn Treebank
Talks
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