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IJCNN
2006
IEEE
16 years 19 days ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
EUROGP
2005
Springer
122views Optimization» more  EUROGP 2005»
16 years 4 days ago
Evolution of Robot Controller Using Cartesian Genetic Programming
Abstract. Cartesian Genetic Programming is a graph based representation that has many benefits over traditional tree based methods, including bloat free evolution and faster evolu...
Simon Harding, Julian F. Miller
GECCO
2004
Springer
110views Optimization» more  GECCO 2004»
15 years 12 months ago
Biomass Inferential Sensor Based on Ensemble of Models Generated by Genetic Programming
A successful industrial application of a novel type biomass estimator based on Genetic Programming (GP) is described in the paper. The biomass is inferred from other available meas...
Arthur K. Kordon, Elsa Jordaan, Lawrence Chew, Gui...
188
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ISNN
2004
Springer
15 years 12 months ago
Evolving Flexible Neural Networks Using Ant Programming and PSO Algorithm
A flexible neural network (FNN) is a multilayer feedforward neural network with the characteristics of: (1) overlayer connections; (2) variable activation functions for different...
Yuehui Chen, Bo Yang, Jiwen Dong
TAPIA
2003
ACM
15 years 12 months ago
A new infeasible interior-point algorithm for linear programming
In this paper we present an infeasible path-following interiorpoint algorithm for solving linear programs using a relaxed notion of the central path, called quasicentral path, as ...
Miguel Argáez, Leticia Velázquez