85 search results - page 2 / 17 » Novel maximum-margin training algorithms for supervised neur... |
IJCNN
2006
IEEE
13 years 10 months ago
2006
IEEE
Abstract— Neural processing of large-scale data sets containing both many input / output variables and a large number of training examples often leads to very large networks. Onc...
GECCO
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
IJCNN
2008
IEEE
13 years 11 months ago
2008
IEEE
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
DATE
2008
IEEE
13 years 11 months ago
2008
IEEE
This paper presents a novel architecture for on-chip neural network training using particle swarm optimization (PSO). PSO is an evolutionary optimization algorithm with a growing ...
SBRN
2002
IEEE
13 years 9 months ago
2002
IEEE
This article presents the system “Neural Connect 4”, a program that plays the game Connect Four. This system employs the multilayer perceptron architecture which is learning t...