In recent years, a number of algorithms have been developed for learning the structure of Bayesian networks from data. In this paper we apply some of these algorithms to a realist...
Xiaofeng Wu, Peter J. F. Lucas, Susan Kerr, Roelf ...
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
— Transmission scheduling is a key design problem in wireless multi-hop networks and many scheduling algorithms have been proposed to maximize the spatial reuse and minimize the ...
The mesh-connected array is an attractive architecture for parallel machines, and a number of existing parallel machines are based on a mesh topology. In this paper, we survey the ...
In this paper we present algorithms for computing the topology of planar and space rational curves defined by a parametrization. The algorithms given here work directly with the p...