Traffic engineering of IP networks requires the characterization and modeling of network traffic on multiple time scales due to the existence of several statistical properties that...
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology,...
Current large-scale topology mapping systems require multiple days to characterize the Internet due to the large amount of probing traffic they incur. The accuracy of maps from ex...
Background: Standard graphs, where each edge links two nodes, have been extensively used to represent the connectivity of metabolic networks. It is based on this representation th...