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IWANN
2005
Springer
13 years 9 months ago
Role of Function Complexity and Network Size in the Generalization Ability of Feedforward Networks
The generalization ability of different sizes architectures with one and two hidden layers trained with backpropagation combined with early stopping have been analyzed. The depend...
Leonardo Franco, José M. Jerez, José...
GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
13 years 8 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
ICGA
1993
145views Optimization» more  ICGA 1993»
13 years 5 months ago
Genetic Programming of Minimal Neural Nets Using Occam's Razor
A genetic programming method is investigated for optimizing both the architecture and the connection weights of multilayer feedforward neural networks. The genotype of each networ...
Byoung-Tak Zhang, Heinz Mühlenbein
BMCBI
2004
111views more  BMCBI 2004»
13 years 3 months ago
Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network
Background: Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes...
Radu Dobrin, Qasim K. Beg, Albert-Lászl&oac...
ISNN
2010
Springer
13 years 2 months ago
Extension of the Generalization Complexity Measure to Real Valued Input Data Sets
Abstract. This paper studies the extension of the Generalization Complexity (GC) measure to real valued input problems. The GC measure, defined in Boolean space, was proposed as a...
Iván Gómez, Leonardo Franco, Jos&eac...