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GECCO
2008
Springer
184views Optimization» more  GECCO 2008»
13 years 8 months ago
Analysis of mammography reports using maximum variation sampling
A genetic algorithm (GA) was developed to implement a maximum variation sampling technique to derive a subset of data from a large dataset of unstructured mammography reports. It ...
Robert M. Patton, Barbara G. Beckerman, Thomas E. ...
GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
14 years 24 days ago
Adaptive Sampling for Noisy Problems
Abstract. The usual approach to deal with noise present in many realworld optimization problems is to take an arbitrary number of samples of the objective function and use the samp...
Erick Cantú-Paz
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
14 years 1 months ago
Best SubTree genetic programming
The result of the program encoded into a Genetic Programming (GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we pres...
Oana Muntean, Laura Diosan, Mihai Oltean
GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
13 years 8 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
GECCO
2006
Springer
182views Optimization» more  GECCO 2006»
13 years 11 months ago
Distributed genetic algorithm for energy-efficient resource management in sensor networks
In this work we consider energy-efficient resource management in an environment monitoring and hazard detection sensor network. Our goal is to allocate different detection methods...
Qinru Qiu, Qing Wu, Daniel J. Burns, Douglas Holzh...