Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...
We have developed a distributed DSS capable to working in a dynamic way. That is, when a domain of an organization needs a new kind of information, the system looks for this infor...
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
In this paper we present the design, implementation and evaluation of SOBA, a system for ontology-based information extraction from heterogeneous data resources, including plain t...
Paul Buitelaar, Philipp Cimiano, Anette Frank, Mat...
Information integration applications, such as mediators or mashups, that require access to information resources currently rely on users manually discovering and integrating them ...