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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
15 years 11 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
191
Voted
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 11 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima
194
Voted
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 11 months ago
A combinatorial genetic algorithm for the configuration of the 2dF/AAOmega spectrograph at the anglo-Australian observatory
To help unravel the structure of the universe, astronomers have developed systems which observe large clusters of objects at the same time. One such system is the 2-degree field s...
Steven Manos, Geraint Lewis
GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
15 years 11 months ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro
175
Voted
GECCO
2006
Springer
154views Optimization» more  GECCO 2006»
15 years 11 months ago
Spectral techniques for graph bisection in genetic algorithms
Various applications of spectral techniques for enhancing graph bisection in genetic algorithms are investigated. Several enhancements to a genetic algorithm for graph bisection a...
Jacob G. Martin
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