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GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 3 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 4 months ago
Towards billion-bit optimization via a parallel estimation of distribution algorithm
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm (cGA) to solve very large scale problems with millions to billions of va...
Kumara Sastry, David E. Goldberg, Xavier Llor&agra...
TSMC
2011
258views more  TSMC 2011»
14 years 4 months ago
Cross-Entropy Optimization of Control Policies With Adaptive Basis Functions
—This paper introduces an algorithm for direct search of control policies in continuous-state discrete-action Markov decision processes. The algorithm looks for the best closed-l...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
TEC
2002
128views more  TEC 2002»
14 years 9 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
TNN
2008
181views more  TNN 2008»
14 years 9 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu