With the explosion of the Internet the World Wide Web today has become an infinite source of information. Hence, it is important that one be able to categorize, understand and be a...
Vishal Anand, Keith Hansen, Radu Jianu, Adrian Rus...
A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...
The paper presents a novel multi-view learning framework based on variational inference. We formulate the framework as a graph representation in form of graph factorization: the g...
In this demo we present a first implementation of Semantic Web Pipes, a powerful tool to build RDF-based mashups. Semantic Web pipes are defined in XML and when executed they fetch...
Christian Morbidoni, Danh Le Phuoc, Axel Polleres,...
We introduce a general method to count and randomly sample unlabeled combinatorial structures. The approach is based on pointing unlabeled structures in an “unbiased” way, i.e...