Richard Maclin
Richard Maclin
Professor of Computer Science, University of Minnesota Duluth
Verified email at d.umn.edu - Homepage
Title
Cited by
Cited by
Year
Popular ensemble methods: An empirical study
D Opitz, R Maclin
Journal of Artificial Intelligence Research 11, 169-198, 1999
27641999
An empirical evaluation of bagging and boosting
R Maclin, D Opitz
AAAI/IAAI 1997, 546-551, 1997
3561997
Creating advice-taking reinforcement learners
R Maclin, JW Shavlik
Machine Learning 22 (1), 251-281, 1996
2621996
Exploiting unlabeled data in ensemble methods
KP Bennett, A Demiriz, R Maclin
Proceedings of the eighth ACM SIGKDD international conference on Knowledge …, 2002
2282002
Combining the predictions of multiple classifiers: Using competitive learning to initialize neural networks
R Maclin, JW Shavlik
IJCAI 95, 524-531, 1995
1611995
Using advice to transfer knowledge acquired in one reinforcement learning task to another
L Torrey, T Walker, J Shavlik, R Maclin
European Conference on Machine Learning, 412-424, 2005
1322005
Giving advice about preferred actions to reinforcement learners via knowledge-based kernel regression
R Maclin, J Shavlik, L Torrey, T Walker, E Wild
AAAI, 819-824, 2005
1222005
Using knowledge-based neural networks to improve algorithms: Refining the Chou-Fasman algorithm for protein folding
R Maclin, JW Shavlik
Machine Learning 11 (2-3), 195-215, 1993
1041993
Popular ensemble methods: An empirical study
R Maclin, D Opitz
ArXiv e-prints, arXiv: 1106.0257, 2011
992011
Incorporating advice into agents that learn from reinforcements
R Maclin, JW Shavlik
University of Wisconsin-Madison. Computer Sciences Department, 1994
841994
Skill acquisition via transfer learning and advice taking
L Torrey, J Shavlik, T Walker, R Maclin
European Conference on Machine Learning, 425-436, 2006
792006
Refining algorithms with knowledge-based neural networks: improving the Chou-Fasman algorithm for protein folding
R Maclin, JW Shavlik
Computational Learning Theory and Natural Learning Systems 1, 249-286, 1992
781992
Relational macros for transfer in reinforcement learning
L Torrey, J Shavlik, T Walker, R Maclin
International Conference on Inductive Logic Programming, 254-268, 2007
732007
Refining domain theories expressed as finite-state automata
R Maclin, JW Shavlik
Machine Learning Proceedings 1991, 524-528, 1991
661991
A Comparative Study of Support Vector Machines Applied to the Supervised Word Sense Disambiguation Problem in the Medical Domain.
M Joshi, T Pedersen, R Maclin
IICAI, 3449-3468, 2005
622005
An empirical evaluation of bagging and boosting for artificial neural networks
DW Opitz, RF Maclin
Proceedings of International Conference on Neural Networks (ICNN'97) 3, 1401 …, 1997
481997
Ensembles as a sequence of classifiers
L Asker, R Maclin
IJCAI (2), 860-865, 1997
361997
Online knowledge-based support vector machines
G Kunapuli, KP Bennett, A Shabbeer, R Maclin, J Shavlik
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010
352010
Boosting classifiers regionally
R Maclin
AAAI/IAAI, 700-705, 1998
351998
Transfer learning via advice taking
L Torrey, J Shavlik, T Walker, R Maclin
Advances in Machine Learning I, 147-170, 2010
252010
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Articles 1–20