Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Abstract. We consider the problem of efficient approximate learning by multilayered feedforward circuits subject to two objective functions. First, we consider the objective to ma...
One challenge faced by many Inductive Logic Programming (ILP) systems is poor scalability to problems with large search spaces and many examples. Randomized search methods such as ...
Abstract. Ontology based data access (OBDA) is concerned with providing access to typically very large data sources through a mediating conceptual layer that allows one to improve ...
Elena Botoeva, Diego Calvanese, Mariano Rodriguez-...