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» Symbolic regression in multicollinearity problems
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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
15 years 3 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 6 months ago
An evolutionary approach to constructive induction for link discovery
This paper presents a genetic programming-based symbolic regression approach to the construction of relational features in link analysis applications. Specifically, we consider t...
Tim Weninger, William H. Hsu, Jing Xia, Waleed Alj...
TAP
2010
Springer
126views Hardware» more  TAP 2010»
15 years 4 months ago
DyGen: Automatic Generation of High-Coverage Tests via Mining Gigabytes of Dynamic Traces
Unit tests of object-oriented code exercise particular sequences of method calls. A key problem when automatically generating unit tests that achieve high structural code coverage ...
Suresh Thummalapenta, Jonathan de Halleux, Nikolai...
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
15 years 3 months ago
Heterogeneous cooperative coevolution: strategies of integration between GP and GA
Cooperative coevolution has proven to be a promising technique for solving complex combinatorial optimization problems. In this paper, we present four different strategies which i...
Leonardo Vanneschi, Giancarlo Mauri, Andrea Valsec...
ICTAI
2009
IEEE
15 years 6 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...