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» Adapting RBF Neural Networks to Multi-Instance Learning
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TNN
2010
234views Management» more  TNN 2010»
13 years 2 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
NN
2002
Springer
13 years 7 months ago
Self-organizing maps with recursive neighborhood adaptation
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to multivariate data analysis. In that context, this paper presents variants of the...
John Aldo Lee, Michel Verleysen
NN
2008
Springer
13 years 7 months ago
Multilayer in-place learning networks for modeling functional layers in the laminar cortex
Currently, there is a lack of general-purpose in-place learning networks that model feature layers in the cortex. By "general-purpose" we mean a general yet adaptive hig...
Juyang Weng, Tianyu Luwang, Hong Lu, Xiangyang Xue
ESANN
2006
13 years 9 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...
IWANN
2005
Springer
14 years 1 months ago
Adaptive Power System Stabilizer Using ANFIS and Genetic Algorithms
— This paper presents an adaptive Power System Stabilizer (PSS) using an Adaptive Network Based Fuzzy Inference System (ANFIS) and Genetic Algorithms (GAs). Firstly, genetic algo...
Jesús Fraile-Ardanuy, Pedro J. Zufiria