— We present a crosslayer framework for optimizing the performance of wireless networks as measured by applications or upper layer protocols. The approach combines adaptive modul...
Daniel O'Neill, Andrea J. Goldsmith, Stephen P. Bo...
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Abstract. We present a game-theoretic framework for modeling and solving routing problems in dynamically changing networks. The model covers the aspects of reactivity and non-termi...
Marques and Almeida [9] recently proposed a nonlinear data seperation technique based on the maximum entropy principle of Bell and Sejnowsky. The idea behind is a pattern repulsion...
Fabian J. Theis, Christoph Bauer, Carlos Garc&iacu...
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...