Feature models are commonly used to capture the commonality and the variability of product families. There are several feature model notations that correspondingly depict the conce...
Abstract: Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about com...
Stefan Schaal, Christopher G. Atkeson, Sethu Vijay...
We present an algebraic framework for evidence exploration: the process of interpreting, manipulating, and navigating the proof structure or evidence produced by a model checker w...
Abstract. Computing the minimal network (or minimal CSP) representation of a given set of constraints over the Point Algebra (PA) is a fundamental reasoning problem. In this paper ...
In this paper we present a method of describing microprocessors at different levels of temporal and data abstraction. We consider microprogrammed, pipelined and superscalar proces...