The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
In STOC 93, Jones sketched the existence of a hierarchy within problems decidable in linear time by a first-order functional language based on tree-structured data (F), as well a...