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TNN
2010
234views Management» more  TNN 2010»
13 years 3 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
NIPS
2004
13 years 10 months ago
Synchronization of neural networks by mutual learning and its application to cryptography
Two neural networks that are trained on their mutual output synchronize to an identical time dependant weight vector. This novel phenomenon can be used for creation of a secure cr...
Einat Klein, Rachel Mislovaty, Ido Kanter, Andreas...
GECCO
2003
Springer
120views Optimization» more  GECCO 2003»
14 years 1 months ago
New Usage of SOM for Genetic Algorithms
Abstract. Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM h...
Jung Hwan Kim, Byung Ro Moon
ESANN
2006
13 years 10 months ago
Evolino for recurrent support vector machines
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...
ESANN
2006
13 years 10 months ago
Magnification control for batch neural gas
Neural gas (NG) constitutes a very robust clustering algorithm which can be derived as stochastic gradient descent from a cost function closely connected to the quantization error...
Barbara Hammer, Alexander Hasenfuss, Thomas Villma...