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» Introduction to artificial neural networks
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APIN
2005
127views more  APIN 2005»
13 years 7 months ago
Evolutionary Radial Basis Functions for Credit Assessment
Credit analysts generally assess the risk of credit applications based on their previous experience. They frequently employ quantitative methods to this end. Among the methods used...
Estefane G. M. de Lacerda, André Carlos Pon...
DAGSTUHL
2003
13 years 9 months ago
Removing Some 'A' from AI: Embodied Cultured Networks
We embodied networks of cultured biological neurons in simulation and in robotics. This is a new research paradigm to study learning, memory, and information processing in real tim...
Douglas J. Bakkum, Alexander C. Shkolnik, Guy Ben-...
HIS
2008
13 years 9 months ago
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
André L. D. Rossi, André C. P. L. F....
GECCO
2005
Springer
141views Optimization» more  GECCO 2005»
14 years 1 months ago
RABNET: a real-valued antibody network for data clustering
This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demons...
Helder Knidel, Leandro Nunes de Castro, Fernando J...
AI
2002
Springer
13 years 7 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang