Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
three levels of abstraction in system modeling. Computation Independent Model (CIM) corresponds to the system's domain model and is similar to the domain ontology. It does not...
— Understanding the behavior of emerging workloads is important for designing next generation microprocessors. For addressing this issue, computer architects and performance anal...
We present a generic transformation that allows us to use a large class of pairing-based signatures to construct schemes for signing group elements in a structure preserving way. A...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...