Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest i...
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...
We consider a key distribution scheme for securing node-to-node communication in sensor networks. While most schemes in use are based on random predistribution, we consider a syste...
Marek Klonowski, Miroslaw Kutylowski, Michal Ren, ...
In this contribution, models of wireless channels are derived from the maximum entropy principle, for several cases where only limited information about the propagation environmen...
Abstract. Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. Th...