This paper describes an approach to robotic control that is patterned after models of human skill acquisition. The intent is to develop robots capable of learning how to accomplis...
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
We propose a generic model for the "weighted voting" aggregation step performed by several methods in supervised classification. Further, we construct an algorithm to en...
Jan Adem, Yves Crama, Willy Gochet, Frits C. R. Sp...