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EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
15 years 6 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...
EUROGP
2010
Springer
182views Optimization» more  EUROGP 2010»
15 years 1 months ago
Unsupervised Problem Decomposition Using Genetic Programming
We propose a new framework based on Genetic Programming (GP) to automatically decompose problems into smaller and simpler tasks. The framework uses GP at two levels. At the top lev...
Ahmed Kattan, Alexandros Agapitos, Riccardo Poli
IWVF
2001
Springer
15 years 4 months ago
Grouping Character Shapes by Means of Genetic Programming
In the framework of an evolutionary approach to machine learning, this paper presents the preliminary version of a learning system that uses Genetic Programming as a tool for autom...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
ACSW
2004
15 years 1 months ago
Applying Online Gradient Descent Search to Genetic Programming for Object Recognition
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...
William D. Smart, Mengjie Zhang
CEC
2010
IEEE
15 years 2 days ago
G3PARM: A Grammar Guided Genetic Programming algorithm for mining association rules
— This paper presents the G3PARM algorithm for mining representative association rules. G3PARM is an evolutionary algorithm that uses G3P (Grammar Guided Genetic Programming) and...
Jose María Luna, José Raúl Ro...