Abstract. In this paper we explore a topic which is at the intersection of two areas of Machine Learning: namely Support Vector Machines (SVMs) and Inductive Logic Programming (ILP...
Stephen Muggleton, Huma Lodhi, Ata Amini, Michael ...
This article advocates a new model for inductive learning. Called sequential induction, it helps bridge classical fixed-sample learning techniques (which are efficient but difficu...
Retiming and resynthesis are among the most important techniques for practical sequential circuit optimization. However, their applicability is much limited due to verification c...
The nominal approach to abstract syntax deals with the issues of bound names and α-equivalence by considering constructions and properties that are invariant with respect to permu...
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...