Genomes are dynamic molecules that are constantly undergoing mutations and rearrangements. The latter are large scale changes in a genome organisation that participate in the evol...
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvant...
The application of network analysis to emergent mating topologies in spatially structured genetic algorithms is presented in this preliminary study as a framework for inferring ev...
We present SETS, an architecture for efficient search in peer-to-peer networks, building upon ideas drawn from machine learning and social network theory. The key idea is to arran...