Distributed Hash Tables (DHTs) bring the promise of increased availability of data to wide-area systems, under the assumption of uniform request load. However, they don't int...
Abstract. Most test-selection algorithms currently in use with probabilistic networks select variables myopically, that is, test variables are selected sequentially, on a one-by-on...
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...
Abstract. In this paper, we present a revision strategy of revising a conditional probabilistic logic program (PLP) when new information is received (which is in the form of probab...
Abstract. This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, g...