Abstract. Current generative programming approaches use configuration knowledge to automatically manufacture an end product given a particular requirements specification. Such conf...
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Inter-domain path computation, or the ability to compute end-to-end paths across multiple domains, is the next step toward wide deployment of a distributed control plane with supp...
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
The Service-Oriented Computing (SOC) paradigm promotes the use of basic composition units – services – to support the rapid development of distributed applications. Service co...