The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
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...
We propose the combination of two recently introduced methods for the interactive visual data mining of large collections of data. Both, Hyperbolic Multi-Dimensional Scaling (HMDS...
This paper presents some interesting results obtained by the algorithm by Bauer, Der and Hermann (BDH) [1] for magnification control in Self-Organizing Maps. Magnification control ...
A self-organized approach to manage a distributed proxy system called Adaptive Distributed Caching (ADC) has been proposed previously. We model each proxy as an autonomous agent th...