We propose a method for dynamic security domain scaling on SMPs that offers both highly scalable performance and high security for future high-end embedded systems. Its most impor...
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
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...
Thirteen years have passed since Karl Sims published his work on evolving virtual creatures. Since then, several novel approaches to neural network evolution and genetic algorithm...
Modern distributed information retrieval techniques require accurate knowledge of collection size. In non-cooperative environments, where detailed collection statistics are not av...