We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
Testing model transformations requires input models which are graphs of inter-connected objects that must conform to a meta-model and meta-constraints from heterogeneous sources su...
o much higher levels of abstraction than today's design practices, which are usually at the level of synthesizable RTL for custom hardware or Instruction Set Simulator (ISS) f...
Mark Genoe, Christopher K. Lennard, Joachim Kunkel...
—In this paper we investigate the static multicast advance reservation (MCAR) problem for all-optical wavelengthrouted WDM networks. Under the advanced reservation traffic model...
Different formal learning models address different aspects of human learning. Below we compare Gold-style learning—interpreting learning as a limiting process in which the lear...