The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transfor...
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindn...
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
YANNS (Yet Another Neural Network Simulator) is a new object-oriented neural network simulator for feedforward networks as well as general recurrent networks. The goal of this pro...
We present an approximate analytical method to compute efficiently the call blocking probabilities in wavelength routing networks with multiple classes of calls. The model is fairl...
Sridhar Ramesh, George N. Rouskas, Harry G. Perros
Wireless sensor networks consist of energy-constrained sensor nodes operating unattended in highly dynamic environments. In this paper, we advocate a systematic decentralized appro...