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GECCO
2006
Springer
202views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolving hash functions by means of genetic programming
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fa...
César Estébanez, Julio César ...
GECCO
2006
Springer
207views Optimization» more  GECCO 2006»
13 years 11 months ago
Both robust computation and mutation operation in dynamic evolutionary algorithm are based on orthogonal design
A robust dynamic evolutionary algorithm (labeled RODEA), where both the robust calculation and mutation operator are based on an orthogonal design, is proposed in this paper. Prev...
Sanyou Y. Zeng, Rui Wang, Hui Shi, Guang Chen, Hug...
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 1 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...
TEC
2008
135views more  TEC 2008»
13 years 6 months ago
Evolving Output Codes for Multiclass Problems
In this paper, we propose an evolutionary approach to the design of output codes for multiclass pattern recognition problems. This approach has the advantage of taking into account...
Nicolás García-Pedrajas, Colin Fyfe
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 8 months ago
Comparison and Analysis of Mutation-based Evolutionary Algorithms for ANN Parameters Optimization
Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...