A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Traditional architectural designs are normally focused on CPUs and have been often decoupled from I/O considerations. They are inefficient for high-speed network processing with a...
Efficient and robust metacomputing requires the decomposition of complex jobs into tasks that must be scheduled on distributed processing nodes. There are various ways of creating...
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...