In traditional mathematical models of argumentation an argument often consists of a chain of rules or reasons, beginning with premisses and leading to a conclusion that is endorse...
Abstract— We consider the following problem of decentralized statistical inference: given i.i.d. samples from an unknown distribution, estimate an arbitrary quantile subject to l...
The Semantic Web drives towards the use of the Web for interacting with logically interconnected data. Through knowledge models such as Resource Description Framework (RDF), the S...
Tim Berners-Lee, Dan Connolly, Lalana Kagal, Yosi ...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms have been...