161 search results - page 16 / 33 » Learning to Map Ontologies with Neural Network |
GECCO
2005
Springer
14 years 28 days ago
2005
Springer
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
ICANN
2011
Springer
12 years 11 months ago
2011
Springer
Currently the most accurate WLAN positioning systems are based on the fingerprinting approach, where a “radio map” is constructed by modeling how the signal strength measureme...
ESANN
2003
13 years 8 months ago
2003
We consider two layered binary state neural networks in which cellular topographic self-organization occurs under correlational learning. The main result is that for separable inpu...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
IJCNN
2008
IEEE
14 years 1 months ago
2008
IEEE
Abstract— This study proposes a Batch-Learning SelfOrganizing Map with False-Neighbor degree between neurons (called BL-FNSOM). False-neighbor degrees are allocated between adjac...