Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
The paper identifies elements in network monitoring systems that cause errors in the load measurements found in recent reports on network statistics from an academic backbone netw...
Interconnection architectures range from complete networks, that have a diameter of D = 1 but are impractical except when the number n of nodes is small, to low-cost, minimally co...
We introduce a new overlay network named ROSA1 . Overlay networks offer a way to bypass the routing constraints of the underlying network. ROSA used this overlay network property t...
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...