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» An Effective Learning Method for Max-Min Neural Networks
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110
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PAKDD
2000
ACM
100views Data Mining» more  PAKDD 2000»
15 years 7 months ago
Discovery of Relevant Weights by Minimizing Cross-Validation Error
In order to discover relevant weights of neural networks, this paper proposes a novel method to learn a distinct squared penalty factor for each weight as a minimization problem ov...
Kazumi Saito, Ryohei Nakano
ICANN
2009
Springer
15 years 10 months ago
Decomposition Methods for Detailed Analysis of Content in ERP Recordings
The processes giving rise to an event related potential engage several evoked and induced oscillatory components, which reflect phase or non-phase locked activity throughout the mu...
Vasiliki Iordanidou, Kostas Michalopoulos, Vangeli...
ECAL
1999
Springer
15 years 8 months ago
Evolution of Neural Controllers with Adaptive Synapses and Compact Genetic Encoding
Abstract. This paper is concerned with arti cial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype ...
Dario Floreano, Joseba Urzelai
TNN
2008
93views more  TNN 2008»
15 years 3 months ago
Towards the Optimal Design of Numerical Experiments
This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
S. Gazut, J.-M. Martinez, Gérard Dreyfus, Y...
127
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IJCNN
2006
IEEE
15 years 10 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö