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» Different Learning Algorithms for Neural Networks - A Compar...
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NPL
2006
137views more  NPL 2006»
13 years 7 months ago
Minimal Structure of Self-Organizing HCMAC Neural Network Classifier
The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Chih-Ming Chen, Yung-Feng Lu, Chin-Ming Hong
EWRL
2008
13 years 9 months ago
Bayesian Reward Filtering
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
DAGM
2007
Springer
13 years 11 months ago
Efficient Learning of Neural Networks with Evolutionary Algorithms
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
Nils T. Siebel, Jochen Krause, Gerald Sommer
HPDC
2006
IEEE
14 years 1 months ago
Peer to peer size estimation in large and dynamic networks: A comparative study
As the size of distributed systems keeps growing, the peer to peer communication paradigm has been identified as the key to scalability. Peer to peer overlay networks are charact...
Erwan Le Merrer, Anne-Marie Kermarrec, Laurent Mas...
BMCBI
2008
174views more  BMCBI 2008»
13 years 7 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...