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GPTP 2014: University of Michigan, Ann Arbor, MI, USA
- Rick L. Riolo, William P. Worzel, Mark E. Kotanchek:
Genetic Programming Theory and Practice XII, [GPTP 2014, University of Michigan, Ann Arbor, USA, May 8-10, 2014]. Springer 2015, ISBN 978-3-319-16029-0 - Chao Cheng, William P. Worzel:
Application of Machine-Learning Methods to Understand Gene Expression Regulation. 1-15 - Jason H. Moore, Casey S. Greene, Douglas P. Hill:
Identification of Novel Genetic Models of Glaucoma Using the "EMERGENT" Genetic Programming-Based Artificial Intelligence System. 17-35 - William G. La Cava, Lee Spector:
Inheritable Epigenetics in Genetic Programming. 37-51 - William P. Worzel, Duncan MacLean:
SKGP: The Way of the Combinator. 53-71 - Luiz Otávio Vilas Boas Oliveira, Fernando E. B. Otero, Gisele L. Pappa, Julio Albinati:
Sequential Symbolic Regression with Genetic Programming. 73-90 - Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner:
Sliding Window Symbolic Regression for Detecting Changes of System Dynamics. 91-107 - Michael F. Korns:
Extremely Accurate Symbolic Regression for Large Feature Problems. 109-131 - Mauro Castelli, Leonardo Vanneschi, Sara Silva, Stefano Ruberto:
How to Exploit Alignment in the Error Space: Two Different GP Models. 133-148 - Karthik Kannappan, Lee Spector, Moshe Sipper, Thomas Helmuth, William G. La Cava, Jake Wisdom, Omri Bernstein:
Analyzing a Decade of Human-Competitive ("HUMIE") Winners: What Can We Learn? 149-166 - Hormoz Shahrzad, Babak Hodjat:
Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System. 167-179
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