We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Abstract: A study of the classes of nite relations as enriched strict monoidal categories is presented in CaS91]. The relations there are interpreted as connections in owchart sche...
Background: We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document ...
One of the main challenges for the development of spatial information theory is the formalization of the concepts of space and spatial relations. Currently, most spatial data struc...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...