We evaluate response times, in N-user collaborations, of the popular centralized (client-server) and replicated (peer-to-peer) architectures, and a hybrid architecture in which ea...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
The automated analysis of model specifications is an area that historically receives little attention in the simulation research community but which can offer significant bene...
Kara A. Olson, C. Michael Overstreet, E. Joseph De...
We consider a system with a dispatcher and several identical servers in parallel. Task processing times are known upon arrival. We first study the impact of the local scheduling ...