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Andrew McCallum
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Conditional random fields: Probabilistic models for segmenting and labeling sequence data
J Lafferty, A McCallum, FCN Pereira
164732001
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
53001998
Text classification from labeled and unlabeled documents using EM
K Nigam, AK McCallum, S Thrun, T Mitchell
Machine learning 39 (2), 103-134, 2000
40402000
Mallet: A machine learning for language toolkit
AK McCallum
http://mallet. cs. umass. edu, 2002
28712002
An introduction to conditional random fields
C Sutton, A McCallum
Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012
24402012
An introduction to conditional random fields
C Sutton, A McCallum
Foundations and Trends® in Machine Learning 4 (4), 267-373, 2012
24372012
Maximum entropy Markov models for information extraction and segmentation.
A McCallum, D Freitag, FCN Pereira
Icml 17 (2000), 591-598, 2000
19632000
Introduction to statistical relational learning
D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ...
MIT press, 2007
18752007
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
17572006
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
16852011
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons
A McCallum, W Li
15272003
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
14922000
Toward optimal active learning through monte carlo estimation of error reduction
N Roy, A McCallum
ICML, Williamstown 2, 441-448, 2001
14292001
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
13291999
Energy and policy considerations for deep learning in NLP
E Strubell, A Ganesh, A McCallum
arXiv preprint arXiv:1906.02243, 2019
12972019
Employing EM and pool-based active learning for text classification
AK McCallumzy, K Nigamy
Proc. International Conference on Machine Learning (ICML), 359-367, 1998
11511998
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
11342010
Distributional clustering of words for text classification
LD Baker, AK McCallum
Proceedings of the 21st annual international ACM SIGIR conference on …, 1998
11071998
Automating the construction of internet portals with machine learning
AK McCallum, K Nigam, J Rennie, K Seymore
Information Retrieval 3 (2), 127-163, 2000
10202000
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
9901998
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