Abstract. Logic Programs with Annotated Disjunctions (LPADs) provide a simple and elegant framework for integrating probabilistic reasoning and logic programming. In this paper we ...
Abstract. This paper introduces Deft, a new multitask learning approach for rule learning algorithms. Like other multitask learning systems, the one proposed here is able to improv...
Recent statistical performance surveys of search algorithms in difficult combinatorial problems have demonstrated the benefits of randomising and restarting the search procedure. ...
Random forest induction is a bagging method that randomly samples the feature set at each node in a decision tree. In propositional learning, the method has been shown to work well...
Celine Vens, Anneleen Van Assche, Hendrik Blockeel...
Abstract. In this paper, we study how a logical form of scientific modelling that integrates together abduction and induction can be used to understand the functional class of unk...
Alireza Tamaddoni-Nezhad, Antonis C. Kakas, Stephe...
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 ...
In this paper, we study the generalization algorithms for second-order terms, which are treated as first-order terms with function variables, under an instantiation order denoted ...
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. Our research has focused on Information Extraction (IE), a task that typically invol...
This paper focuses on inductive learning of recursive logical theories from a set of examples. This is a complex task where the learning of one predicate definition should be inter...
Margherita Berardi, Antonio Varlaro, Donato Malerb...