Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
Many large scale systems, like grids and structured peer to peer systems, operate on a constrained topology. Since underlying networks do not expose the real topology to the appli...
Today there is a relatively large body of work on automatic acquisition of lexicosyntactical preferences (subcategorization) from corpora. Various techniques have been developed t...
We present fault localization techniques suitable for diagnosing end-to-end service problems in communication systems with complex topologies. We refine a layered system model th...