Andrew McCallum

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	总计	2017 年至今
引用	90894	34211
h 指数	114	76
i10 指数	281	214

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Charles SuttonGoogle, University of Edinburgh在 inf.ed.ac.uk 的电子邮件经过验证
David MimnoAssociate Professor, Cornell University在 cornell.edu 的电子邮件经过验证
Sebastian RiedelProfessor @ University College London, Researcher @ Facebook AI Research在 cs.ucl.ac.uk 的电子邮件经过验证
Aron CulottaAssociate Professor of Computer Science, Tulane University在 tulane.edu 的电子邮件经过验证
Emma StrubellAssistant Professor, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Xuerui WangUber Technologies, Inc.在 uber.com 的电子邮件经过验证
Michael WickUniversity of Massachusetts在 cs.umass.edu 的电子邮件经过验证
Rajarshi DasUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Luke VilnisResearch Scientist, Google在 cs.umass.edu 的电子邮件经过验证
Sameer SinghAssociate Professor, University of California Irvine在 uci.edu 的电子邮件经过验证
David BelangerResearch Scientist, Google Brain在 google.com 的电子邮件经过验证
Pat VergaResearch Scientist Google在 google.com 的电子邮件经过验证
Hanna WallachPartner Research Manager, Microsoft Research在 dirichlet.net 的电子邮件经过验证
Nicholas MonathResearch Scientist, Google在 google.com 的电子邮件经过验证
Dayne FreitagProgram Director, SRI International在 ai.sri.com 的电子邮件经过验证
Manzil ZaheerGoogle Research在 cmu.edu 的电子邮件经过验证
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Andrew McCallum

Distinguished Professor of Computer Science, University of Massachusetts Amherst

在 cs.umass.edu 的电子邮件经过验证 - 首页

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


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Conditional random fields: Probabilistic models for segmenting and labeling sequence data J Lafferty, A McCallum, FCN Pereira	16589	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	5314	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	4032	2000
Mallet: A machine learning for language toolkit AK McCallum http://mallet. cs. umass. edu, 2002	2902	2002
An introduction to conditional random fields C Sutton, A McCallum Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012	2418	2012
Maximum entropy Markov models for information extraction and segmentation. A McCallum, D Freitag, FCN Pereira Icml 17 (2000), 591-598, 2000	1965	2000
Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1888	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	1768	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	1724	2011
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons A McCallum, W Li	1527	2003
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	1493	2000
Toward optimal active learning through monte carlo estimation of error reduction N Roy, A McCallum ICML, Williamstown 2, 441-448, 2001	1446	2001
Energy and policy considerations for deep learning in NLP E Strubell, A Ganesh, A McCallum arXiv preprint arXiv:1906.02243, 2019	1436	2019
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	1336	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	1154	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	1147	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	1051	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	985	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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