Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural...
This paper considers the problem of computer user support and workplace learning in general. Theoretically our work is influenced by ideas on knowledge management, expertise netwo...
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
We describe the integration of smart digital objects with Hebbian learning to create a distributed, real-time, scalable approach to adapting to a community's preferences. We ...
Thomas Lutkenhouse, Michael L. Nelson, Johan Bolle...
Abstract. A spiking neural network modeling the cerebellum is presented. The model, consisting of more than 2000 conductance-based neurons and more than 50 000 synapses, runs in re...
Christian Boucheny, Richard R. Carrillo, Eduardo R...