Andrew McCallum

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Kamal NigamGoogleVerified email at kamalnigam.com
Fernando PereiraVP, GoogleVerified email at google.com
Charles SuttonGoogle, University of EdinburghVerified email at inf.ed.ac.uk
David MimnoAssociate Professor, Cornell UniversityVerified email at cornell.edu
Sebastian RiedelHonorary Professor @ University College London, Researcher @ DeepMindVerified email at cs.ucl.ac.uk
Emma StrubellAssistant Professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Aron CulottaAssociate Professor of Computer Science, Tulane UniversityVerified email at tulane.edu
Xuerui WangUber Technologies, Inc.Verified email at uber.com
Michael WickUniversity of MassachusettsVerified email at cs.umass.edu
Rajarshi DasAWS AI LabsVerified email at cs.washington.edu
Nicholas MonathResearch Scientist, GoogleVerified email at google.com
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Luke VilnisResearch Scientist, GoogleVerified email at google.com
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Sameer SinghAssociate Professor, University of California IrvineVerified email at uci.edu
David BelangerResearch Scientist, Google BrainVerified email at google.com
Pat VergaResearch Scientist GoogleVerified email at google.com
Hanna WallachPartner Research Manager, Microsoft ResearchVerified email at dirichlet.net
Dayne FreitagProgram Director, SRI InternationalVerified email at ai.sri.com
Gregory DruckGraphiteVerified email at graphitehq.com

Andrew McCallum

Distinguished Professor of Computer Science, University of Massachusetts Amherst

Verified email at cs.umass.edu - Homepage

Machine Learning Natural Language Processing Information Extraction Artificial Intelligence Social Network Analysis


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Conditional random fields: Probabilistic models for segmenting and labeling sequence data J Lafferty, A McCallum, FCN Pereira	18042	2001
A comparison of event models for naive bayes text classification A McCallum, K Nigam AAAI-98 workshop on learning for text categorization 752 (1), 41-48, 1998	5640	1998
Text classification from labeled and unlabeled documents using EM K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39, 103-134, 2000	4236	2000
Mallet: A machine learning for languagetoolkit AK McCallum http://mallet. cs. umass. edu, 2002	3100	2002
An introduction to conditional random fields C Sutton, A McCallum Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012	2638	2012
Energy and policy considerations for deep learning in NLP E Strubell, A Ganesh, A McCallum arXiv preprint arXiv:1906.02243, 2019	2462	2019
Optimizing semantic coherence in topic models D Mimno, H Wallach, E Talley, M Leenders, A McCallum Proceedings of the 2011 conference on empirical methods in natural language …, 2011	2219	2011
Maximum entropy Markov models for information extraction and segmentation. A McCallum, D Freitag, FCN Pereira Icml 17 (2000), 591-598, 2000	2066	2000
Topics over time: a non-markov continuous-time model of topical trends X Wang, A McCallum Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006	1888	2006
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons A McCallum, W Li	1639	2003
Toward optimal active learning through monte carlo estimation of error reduction N Roy, A McCallum ICML, Williamstown 2, 441-448, 2001	1605	2001
Efficient clustering of high-dimensional data sets with application to reference matching A McCallum, K Nigam, LH Ungar Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000	1573	2000
Modeling relations and their mentions without labeled text S Riedel, L Yao, A McCallum Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010	1395	2010
Using maximum entropy for text classification K Nigam, J Lafferty, A McCallum IJCAI-99 workshop on machine learning for information filtering 1 (1), 61-67, 1999	1389	1999
Automating the construction of internet portals with machine learning AK McCallum, K Nigam, J Rennie, K Seymore Information Retrieval 3, 127-163, 2000	1316	2000
Employing EM and Pool-Based Active Learning for Text Classification. A McCallum, K Nigam ICML 98, 350-358, 1998	1236	1998
Distributional clustering of words for text classification LD Baker, AK McCallum Proceedings of the 21st annual international ACM SIGIR conference on …, 1998	1112	1998
Learning to extract symbolic knowledge from the World Wide Web M Craven, D DiPasquo, D Freitag, A McCallum, T Mitchell, K Nigam, ... AAAI/IAAI 3 (3.6), 2, 1998	1025	1998
Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering AK McCallum CMU: Pittsburgh, PA, 1996	956*	1996
Rethinking LDA: Why priors matter H Wallach, D Mimno, A McCallum Advances in neural information processing systems 22, 2009	939	2009

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