Mark Craven
Mark Craven
Professor of Biostatistics and Medical Informatics, University of Wisconsin
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
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
An analysis of active learning strategies for sequence labeling tasks
B Settles, M Craven
Proceedings of the 2008 Conference on Empirical Methods in Natural Language …, 2008
Constructing biological knowledge bases by extracting information from text sources.
M Craven, J Kumlien
ISMB 1999, 77-86, 1999
Extracting tree-structured representations of trained networks
M Craven, J Shavlik
Advances in neural information processing systems 8, 24-30, 1995
Learning to construct knowledge bases from the World Wide Web
M Craven, D DiPasquo, D Freitag, A McCallum, T Mitchell, K Nigam, ...
Artificial intelligence 118 (1-2), 69-113, 2000
Multiple-instance active learning
B Settles, M Craven, S Ray
Advances in neural information processing systems 20, 1289-1296, 2007
Incorporating domain knowledge into topic modeling via Dirichlet forest priors
D Andrzejewski, X Zhu, M Craven
Proceedings of the 26th annual international conference on machine learning …, 2009
Using Sampling and Queries to Extract Rules from
MW Craven, JW Shavlik
Machine Learning Proceedings 1994: Proceedings of the Eighth International …, 1994
Using sampling and queries to extract rules from trained neural networks
MW Craven, JW Shavlik
Machine learning proceedings 1994, 37-45, 1994
Using neural networks for data mining
MW Craven, JW Shavlik
Future generation computer systems 13 (2-3), 211-229, 1997
Extracting comprehensible models from trained neural networks
MW Craven
University of Wisconsin-Madison Department of Computer Sciences, 1996
Identification of toxicologically predictive gene sets using cDNA microarrays
RS Thomas, DR Rank, SG Penn, GM Zastrow, KR Hayes, K Pande, ...
Molecular Pharmacology 60 (6), 1189-1194, 2001
Supervised versus multiple instance learning: An empirical comparison
S Ray, M Craven
Proceedings of the 22nd international conference on Machine learning, 697-704, 2005
Active learning with real annotation costs
B Settles, M Craven, L Friedland
Proceedings of the NIPS workshop on cost-sensitive learning 1, 2008
Hierarchical hidden markov models for information extraction
M Skounakis, M Craven, S Ray
IJCAI, 427-433, 2003
Representing sentence structure in hidden Markov models for information extraction
S Ray, M Craven
International Joint Conference on Artificial Intelligence 17 (1), 1273-1279, 2001
Relational learning with statistical predicate invention: Better models for hypertext
M Craven, S Slattery
Machine Learning 43 (1), 97-119, 2001
Learning symbolic rules using artificial neural networks
MW Craven, JW Shavlik
Proceedings of the Tenth International Conference on Machine Learning, 73-80, 1993
A framework for incorporating general domain knowledge into latent dirichlet allocation using first-order logic
D Andrzejewski, X Zhu, M Craven, B Recht
IJCAI Proceedings-International Joint Conference on Artificial Intelligence …, 2011
A Bayesian network approach to operon prediction
J Bockhorst, M Craven, D Page, J Shavlik, J Glasner
Bioinformatics 19 (10), 1227-1235, 2003
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Artikkelit 1–20