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» Weight initialization methods for multilayer feedforward
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ESANN
2001
13 years 6 months ago
Weight initialization methods for multilayer feedforward
In this paper, we present the results of an experimental comparison among seven different weight initialization methods in twelve different problems. The comparison is performed by...
Mercedes Fernández-Redondo, Carlos Hern&aac...
EUROGP
2004
Springer
170views Optimization» more  EUROGP 2004»
13 years 9 months ago
Comparing Hybrid Systems to Design and Optimize Artificial Neural Networks
Abstract. In this paper we conduct a comparative study between hybrid methods to optimize multilayer perceptrons: a model that optimizes the architecture and initial weights of mul...
Pedro A. Castillo Valdivieso, Maribel Garcí...
NCA
2006
IEEE
13 years 5 months ago
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...
Vassilis P. Plagianakos, George D. Magoulas, Micha...
FLAIRS
2006
13 years 6 months ago
Fast Generation of a Sequence of Trained and Validated Feed-Forward Networks
In this paper, three approaches are presented for generating and validating sequences of different size neural nets. First, a growing method is given along with several weight ini...
Pramod Lakshmi Narasimha, Walter Delashmit, Michae...
ICGA
1993
145views Optimization» more  ICGA 1993»
13 years 6 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