Genetic Programming Bibliography entries for Michael Korns
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GP coauthors/coeditors:
Loryfel Nunez,
Tim May,
Philip D Truscott,
Genetic Programming conference papers by Michael Korns
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Michael Korns.
Feature Discovery with Deep Learning Algebra Networks. In
Wolfgang Banzhaf and Leonardo Trujillo and Stephan Winkler and Bill Worzel editors,
Genetic Programming Theory and Practice XVIII, pages 109-127, East Lansing, USA, 2021. Springer.
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Michael F. Korns and Tim May.
Strong Typing, Swarm Enhancement, and Deep Learning Feature Selection in the Pursuit of Symbolic Regression-Classification. In
Wolfgang Banzhaf and Lee Spector and Leigh Sheneman editors,
Genetic Programming Theory and Practice XVI, pages 58-84, Ann Arbor, USA, 2018. Springer.
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Michael F. Korns.
Genetic Programming Symbolic Classification: A Study. In
Wolfgang Banzhaf and Randal S. Olson and William Tozier and Rick Riolo editors,
Genetic Programming Theory and Practice XV, pages 39-54, University of Michigan in Ann Arbor, USA, 2017. Springer.
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Michael F. Korns.
Evolutionary Linear Discriminant Analysis for Multiclass Classification Problems. In
Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 233-234, Berlin, Germany, 2017. ACM.
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Michael F. Korns.
An Evolutionary Algorithm for Big Data Multi-class Classification Problems. In
Rick Riolo and Bill Worzel and Brian Goldman and Bill Tozier editors,
Genetic Programming Theory and Practice XIV, pages 165-178, Ann Arbor, USA, 2016. Springer.
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Phil Truscott and Michael F. Korns.
Predicting Product Choice with Symbolic Regression and Classification. In
Rick Riolo and William P. Worzel and M. Kotanchek and A. Kordon editors,
Genetic Programming Theory and Practice XIII, pages 203-217, Ann Arbor, USA, 2015. Springer.
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Michael Korns.
Highly Accurate Symbolic Regression with Noisy Training Data. In
Rick Riolo and William P. Worzel and M. Kotanchek and A. Kordon editors,
Genetic Programming Theory and Practice XIII, pages 91-115, Ann Arbor, USA, 2015. Springer.
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Michael F. Korns.
Extremely Accurate Symbolic Regression for Large Feature Problems. In
Rick Riolo and William P. Worzel and Mark Kotanchek editors,
Genetic Programming Theory and Practice XII, pages 109-131, Ann Arbor, USA, 2014. Springer.
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Michael F. Korns.
Symbolic regression using abstract expression grammars. In
Lihong Xu and Erik D. Goodman and Guoliang Chen and Darrell Whitley and Yongsheng Ding editors,
GEC '09: Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation, pages 859-862, Shanghai, China, 2009. ACM.
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Michael F. Korns.
Mutation and crossover with abstract expression grammars. In
Anna I. Esparcia and Ying-ping Chen and Gabriela Ochoa and Ender Ozcan and Marc Schoenauer and Anne Auger and Hans-Georg Beyer and Nikolaus Hansen and Steffen Finck and Raymond Ros and Darrell Whitley and Garnett Wilson and Simon Harding and W. B. Langdon and Man Leung Wong and Laurence D. Merkle and Frank W. Moore and Sevan G. Ficici and William Rand and Rick Riolo and Nawwaf Kharma and William R. Buckley and Julian Miller and Kenneth Stanley and Jaume Bacardit and Will Browne and Jan Drugowitsch and Nicola Beume and Mike Preuss and Stephen L. Smith and Stefano Cagnoni and Jim DeLeo and Alexandru Floares and Aaron Baughman and Steven Gustafson and Maarten Keijzer and Arthur Kordon and Clare Bates Congdon and Laurence D. Merkle and Frank W. Moore editors,
GECCO-2009 Symbolic regression and modeling workshop (SRM), pages 2219-2224, Montreal, 2009. ACM.
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Genetic Programming book chapters by Michael Korns
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Michael F. Korns.
Trading Volatility Using Highly Accurate Symbolic Regression. In
Amir H. Gandomi and Amir H. Alavi and Conor Ryan editors,
Handbook of Genetic Programming Applications, pages 531-547. Springer, 2015.
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Philip Truscott and Michael F. Korns.
Explaining Unemployment Rates with Symbolic Regression. In
Rick Riolo and Jason H. Moore and Mark Kotanchek editors,
Genetic Programming Theory and Practice XI, chapter 7, pages 119-135. Springer, Ann Arbor, USA, 2013.
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Michael F. Korns.
Extreme Accuracy in Symbolic Regression. In
Rick Riolo and Jason H. Moore and Mark Kotanchek editors,
Genetic Programming Theory and Practice XI, chapter 1, pages 1-30. Springer, Ann Arbor, USA, 2013.
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Michael F. Korns.
A Baseline Symbolic Regression Algorithm. In
Rick Riolo and Ekaterina Vladislavleva and Marylyn D. Ritchie and Jason H. Moore editors,
Genetic Programming Theory and Practice X, chapter 9, pages 117-137. Springer, Ann Arbor, USA, 2012.
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Philip D. Truscott and Michael F. Korns.
Detecting Shadow Economy Sizes with Symbolic Regression. In
Rick Riolo and Ekaterina Vladislavleva and Jason H. Moore editors,
Genetic Programming Theory and Practice IX, chapter 11, pages 195-210. Springer, Ann Arbor, USA, 2011.
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Michael F. Korns.
Accuracy in Symbolic Regression. In
Rick Riolo and Ekaterina Vladislavleva and Jason H. Moore editors,
Genetic Programming Theory and Practice IX, chapter 8, pages 129-151. Springer, Ann Arbor, USA, 2011.
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Michael F. Korns.
Abstract Expression Grammar Symbolic Regression. In
Rick Riolo and Trent McConaghy and Ekaterina Vladislavleva editors,
Genetic Programming Theory and Practice VIII, volume 8 of Genetic and Evolutionary Computation, chapter 7, pages 109-128. Springer, Ann Arbor, USA, 2010.
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Michael F. Korns.
Symbolic Regression of Conditional Target Expressions. In
Rick L. Riolo and Una-May O'Reilly and Trent McConaghy editors,
Genetic Programming Theory and Practice VII, chapter 13, pages 211-228. Springer, Ann Arbor, 2009.
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Michael F. Korns and Loryfel Nunez.
Profiling Symbolic Regression-Classification. In
Rick L. Riolo and Terence Soule and Bill Worzel editors,
Genetic Programming Theory and Practice VI, chapter 14, pages 215-229. Springer, Ann Arbor, 2008.
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Michael F. Korns.
Large-Scale, Time-Constrained Symbolic Regression-Classification. In
Rick L. Riolo and Terence Soule and Bill Worzel editors,
Genetic Programming Theory and Practice V, chapter 4, pages 53-68. Springer, Ann Arbor, 2007.
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Michael F. Korns.
Large-Scale, Time-Constrained Symbolic Regression. In
Rick L. Riolo and Terence Soule and Bill Worzel editors,
Genetic Programming Theory and Practice IV, volume 5 of Genetic and Evolutionary Computation, pages 299-314. Springer, Ann Arbor, 2006.
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