Andrew McCallum

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Kamal NigamGoogleVerified email at kamalnigam.com
Charles SuttonGoogle, University of EdinburghVerified email at inf.ed.ac.uk
Fernando PereiraVP, GoogleVerified email at google.com
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
Nicholas MonathResearch Scientist, GoogleVerified email at google.com
Rajarshi DasAWS AI LabsVerified email at cs.washington.edu
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Michael WickUniversity of MassachusettsVerified email at cs.umass.edu
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Luke VilnisResearch Scientist, Google DeepMindVerified email at google.com
Sameer SinghAssociate Professor, UC IrvineVerified email at uci.edu
David BelangerResearch Scientist, Google BrainVerified email at google.com
Pat VergaCohereVerified email at cohere.com
Haw-Shiuan ChangUMass AmherstVerified email at cs.umass.edu
Hanna WallachPartner Research Manager, Microsoft ResearchVerified email at dirichlet.net
Dayne FreitagProgram Director, SRI InternationalVerified email at ai.sri.com

Andrew McCallum

Distinguished Professor of Computer Science, University of Massachusetts Amherst

Verified email at cs.umass.edu - Homepage

Machine Learning Natural Language Processing Artificial Intelligence Peer Review


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Conditional random fields: Probabilistic models for segmenting and labeling sequence data J Lafferty, A McCallum, F Pereira Icml 1 (2), 3, 2001	18939	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	5908	1998
Text classification from labeled and unlabeled documents using EM K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39, 103-134, 2000	4331	2000
Energy and policy considerations for modern deep learning research E Strubell, A Ganesh, A McCallum Proceedings of the AAAI conference on artificial intelligence 34 (09), 13693 …, 2020	3847	2020
Mallet: A machine learning for languagetoolkit AK McCallum http://mallet. cs. umass. edu, 2002	3223	2002
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	2613	2011
Maximum entropy Markov models for information extraction and segmentation. A McCallum, D Freitag, FCN Pereira Icml 17 (2000), 591-598, 2000	2138	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	1933	2006
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons A McCallum, W Li	1717	2003
Toward optimal active learning through monte carlo estimation of error reduction N Roy, A McCallum Icml, williamstown 2 (441-448), 4, 2001	1707	2001
Automating the construction of internet portals with machine learning AK McCallum, K Nigam, J Rennie, K Seymore Information Retrieval 3, 127-163, 2000	1629	2000
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	1616	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	1604	2010
An introduction to conditional random fields C Sutton, A McCallum Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012	1543	2012
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	1416	1999
An introduction to conditional random fields for relational learning C Sutton Introduction to statistical relational learning, 2007	1343	2007
Employing EM and Pool-Based Active Learning for Text Classification. AK McCallum, K Nigam ICML 98, 350-358, 1998	1295	1998
Distributional clustering of words for text classification LD Baker, AK McCallum Proceedings of the 21st annual international ACM SIGIR conference on …, 1998	1131	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	1086	1998
Rethinking LDA: Why priors matter H Wallach, D Mimno, A McCallum Advances in neural information processing systems 22, 2009	1011	2009

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