We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples the joint probability distribution of...
This paper presents a novel approach to clustering using an accuracy-based Learning Classifier System. Our approach achieves this by exploiting the generalization mechanisms inher...
The available concept-learners only partially fulfill the needs imposed by the learning apprentice generation of learners. We present a novel approach to interactive concept-learni...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
The techniques for making decisions, i.e., branching, play a central role in complete methods for solving structured CSP instances. In practice, there are cases when SAT solvers be...