ICANN
2005
Springer
13 years 10 months ago
2005
Springer
This paper aims to propose an extension of SOMs called an “SOM of SOMs,” or SOM¾ , in which the mapped objects are self-organizing maps themselves. In SOM¾ , each nodal unit ...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Two recently proposed approaches to recognize temporal patterns have been proposed by J¨ager with the so called Echo State Network (ESN) and by Maass with the so called Liquid Sta...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause cohere...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is b...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Dynamic neural filters (DNFs) are recurrent networks of binary neurons. Under proper conditions of their synaptic matrix they are known to generate exponentially large c...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
This research employs unsupervised pattern recognition to approach the thorny issue of detecting anomalous network behavior. It applies a connectionist model to identify user behav...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
The power iteration is a classical method for computing the eigenvector associated with the largest eigenvalue of a matrix. The subspace iteration is an extension of the power iter...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
We describe a kernel method which uses the maximization of Onicescu’s informational energy as a criteria for computing the relevances of input features. This adaptive relevance d...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...