Patterns are concise, but rich in semantic, representation of data. The approaches proposed in the literature to cope with pattern management problems usually deal with a single ty...
Model coupling is a nontrivial task that is not adequately supported in existing frameworks. Our long term goal is to support the fast-prototyping of model couplings, enabling sci...
This paper discusses an extended adaptive supply network simulation model that explicitly captures growth (in terms of change in size over time, and birth and death) based on Utte...
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
Mixed-initiativesystemspresent the challengeof finding an effective level of interaction betweenhumans and computers. Machinelearning presents a promising approachto this problemi...