Constructive induction divides the problem of learning an inductive hypothesis into two intertwined searches: one—for the “best” representation space, and two—for the “be...
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 address the problem of pool based active learning, and provide an algorithm, called UPAL, that works by minimizing the unbiased estimator of the risk of a hypothe...
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz