Richard Maclin - researchr alias

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Viewing Publication 1 - 33 from 33

2017

Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational DataZhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa, Richard Maclin, David Page. kdd 2017: 1537-1546 [doi]

2011

Advice Refinement in Knowledge-Based SVMsGautam Kunapuli, Richard Maclin, Jude W. Shavlik. nips 2011: 1728-1736 [doi]

2010

Online Knowledge-Based Support Vector MachinesGautam Kunapuli, Kristin P. Bennett, Amina Shabbeer, Richard Maclin, Jude W. Shavlik. pkdd 2010: 145-161 [doi]

Transfer Learning via Advice TakingLisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin. In Jacek Koronacki, Zbigniew W. Ras, Slawomir T. Wierzchon, Janusz Kacprzyk, editors, Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S. Michalski. Volume 262 of Studies in Computational Intelligence, pages 147-170, Springer, 2010. [doi]

Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background KnowledgeTrevor Walker, Ciaran O Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik. ilp 2011: 253-268 [doi]

2008

Advice Taking and Transfer Learning: Naturally Inspired Extensions to Reinforcement LearningLisa Torrey, Trevor Walker, Richard Maclin, Jude W. Shavlik. aaaifs 2008: 103-110 [doi]

Rule Extraction for Transfer LearningLisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin. In Joachim Diederich, editor, Rule Extraction from Support Vector Machines. Volume 80 of Studies in Computational Intelligence, pages 67-82, Springer, 2008. [doi]

2007

2006

2005

2002

Exploiting unlabeled data in ensemble methodsKristin P. Bennett, Ayhan Demiriz, Richard Maclin. kdd 2002: 289-296 [doi]

1999

Popular Ensemble Methods: An Empirical StudyDavid W. Opitz, Richard Maclin. jair, 11:169-198, 1999. [doi]

1998

Boosting Classifiers RegionallyRichard Maclin. AAAI 1998: 700-705

Creating Advice-Taking Reinforcement LearnersRichard Maclin, Jude W. Shavlik. In Sebastian Thrun, Lorien Y. Pratt, editors, Learning to Learn. pages 311-347, Springer, 1998. [doi]

1997

Ensembles as a Sequence of ClassifiersLars Asker, Richard Maclin. IJCAI 1997: 860-865

Feature Engineering and Classifier Selection: A Case Study in Venusian Volcano DetectionLars Asker, Richard Maclin. icml 1997: 3-11

An Empirical Evaluation of Bagging and BoostingRichard Maclin, David W. Opitz. AAAI 1997: 546-551

An empirical evaluation of bagging and boosting for artificial neural networksDavid W. Opitz, Richard Maclin. icnn 1997: 1401-1405 [doi]

1996

Creating Advice-Taking Reinforcement LearnersRichard Maclin, Jude W. Shavlik. ml, 22(1-3):251-281, 1996.

1995

Combining the Predictions of Multiple Classifiers: Using Competitive Learning to Initialize Neural NetworksRichard Maclin, Jude W. Shavlik. IJCAI 1995: 524-531

1994

Incorporating Advice into Agents that Learn from ReinforcementsRichard Maclin, Jude W. Shavlik. AAAI 1994: 694-699

1993

Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein FoldingRichard Maclin, Jude W. Shavlik. ml, 11:195-215, 1993.

1992

Using Knowledge-Based Neural Networks to Improve Algorithms: Refining the Chou-Fasman Algorithm for Protein FoldingRichard Maclin, Jude W. Shavlik. AAAI 1992: 165-170

1991

Refining Domain Theories Expressed as Finite-State AutomataRichard Maclin, Jude W. Shavlik. icml 1991: 524-528

1989

Enriching Vocabularies by Generalizing Explanation StructuresRichard Maclin, Jude W. Shavlik. icml 1989: 444-446

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