Andrew McCallum

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Kamal NigamGoogleAdresse e-mail validée de kamalnigam.com
Fernando PereiraVP, GoogleAdresse e-mail validée de google.com
Charles SuttonGoogle, University of EdinburghAdresse e-mail validée de inf.ed.ac.uk
David MimnoAssociate Professor, Cornell UniversityAdresse e-mail validée de cornell.edu
Sebastian RiedelProfessor @ University College London, Researcher @ Facebook AI ResearchAdresse e-mail validée de cs.ucl.ac.uk
Aron CulottaAssociate Professor of Computer Science, Tulane UniversityAdresse e-mail validée de tulane.edu
Emma StrubellAssistant Professor, Carnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Xuerui WangUber Technologies, Inc.Adresse e-mail validée de uber.com
Michael WickUniversity of MassachusettsAdresse e-mail validée de cs.umass.edu
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Rajarshi DasUniversity of WashingtonAdresse e-mail validée de cs.washington.edu
Luke VilnisResearch Scientist, GoogleAdresse e-mail validée de cs.umass.edu
Sameer SinghAssociate Professor, University of California IrvineAdresse e-mail validée de uci.edu
Dayne FreitagProgram Director, SRI InternationalAdresse e-mail validée de ai.sri.com
David BelangerResearch Scientist, Google BrainAdresse e-mail validée de google.com
Pat VergaResearch Scientist GoogleAdresse e-mail validée de google.com
Nicholas MonathResearch Scientist, GoogleAdresse e-mail validée de google.com
Hanna WallachPartner Research Manager, Microsoft ResearchAdresse e-mail validée de dirichlet.net
Manzil ZaheerGoogle ResearchAdresse e-mail validée de cmu.edu
Haw-Shiuan ChangSchool of Computer Science, UMass, AmherstAdresse e-mail validée de cs.umass.edu

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Andrew McCallum

Distinguished Professor of Computer Science, University of Massachusetts Amherst

Adresse e-mail validée de cs.umass.edu - Page d'accueil

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


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Conditional random fields: Probabilistic models for segmenting and labeling sequence data J Lafferty, A McCallum, FCN Pereira	16710	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	5361	1998
Text classification from labeled and unlabeled documents using EM K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39 (2), 103-134, 2000	4052	2000
Mallet: A machine learning for language toolkit AK McCallum http://mallet. cs. umass. edu, 2002	2922	2002
An introduction to conditional random fields C Sutton, A McCallum Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012	2436	2012
Maximum entropy Markov models for information extraction and segmentation. A McCallum, D Freitag, FCN Pereira Icml 17 (2000), 591-598, 2000	1978	2000
Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1895	2007
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	1783	2006
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	1762	2011
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons A McCallum, W Li	1538	2003
Energy and policy considerations for deep learning in NLP E Strubell, A Ganesh, A McCallum arXiv preprint arXiv:1906.02243, 2019	1515	2019
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	1499	2000
Toward optimal active learning through monte carlo estimation of error reduction N Roy, A McCallum ICML, Williamstown 2, 441-448, 2001	1461	2001
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	1344	1999
Modeling relations and their mentions without labeled text S Riedel, L Yao, A McCallum Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010	1178	2010
Employing EM and pool-based active learning for text classification AK McCallumzy, K Nigamy Proc. International Conference on Machine Learning (ICML), 359-367, 1998	1155	1998
Distributional clustering of words for text classification LD Baker, AK McCallum Proceedings of the 21st annual international ACM SIGIR conference on …, 1998	1097	1998
Automating the construction of internet portals with machine learning AK McCallum, K Nigam, J Rennie, K Seymore Information Retrieval 3 (2), 127-163, 2000	1066	2000
Learning to extract symbolic knowledge from the World Wide Web M Craven, A McCallum, D PiPasquo, T Mitchell, D Freitag Carnegie-mellon univ pittsburgh pa school of computer Science, 1998	989	1998
Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering AK McCallum CMU: Pittsburgh, PA, 1996	936*	1996

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