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» A Statistical Learning Perspective of Genetic Programming
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EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
13 years 11 months ago
A Statistical Learning Perspective of Genetic Programming
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...
Nur Merve Amil, Nicolas Bredeche, Christian Gagn&e...
HIS
2008
13 years 6 months ago
Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining
This paper introduces a multiobjective grammar based genetic programming algorithm to solve a Web Mining problem from multiple instance perspective. This algorithm, called MOG3P-MI...
Amelia Zafra, Eva Lucrecia Gibaja Galindo, Sebasti...
GECCO
2010
Springer
182views Optimization» more  GECCO 2010»
13 years 9 months ago
Model selection in genetic programming
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
Cruz E. Borges, César Luis Alonso, Jos&eacu...

Book
452views
15 years 3 months ago
Practical Artificial Intelligence Programming With Java
This book shows how to implement some AI techniques in java such as Search, Reasoning, Semantic Web, Expert Systems, Genetic Algorithms, Neural Networks, Machine Learning with Weka...
Mark Watson
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
13 years 10 months ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...