We propose a conservative extension of HM(X), a generic constraint-based type inference framework, with bounded existential (a.k.a. abstract) and universal (a.k.a. polymorphic) da...
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
We describe BE, an implemented system for solving belief change problems in the presence of actions. We illustrate how we can use BE to compute the result of belief progression, be...
Relational databases have had great industrial success in computer science, their power evidenced by theoretical analysis and widespread adoption. Often, automated theorem provers...
Abstract. Based on a new, general formulation of the geometric method of moving frames, invariantization of numerical schemes has been established during the last years as a powerf...