Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
Abstract. The design of survivable mesh based STM networks has received considerable attention in recent years and is a complex multiconstraint optimization problem. In this paper,...
Adel Al-Rumaih, David Tipper, Yu Liu, Bryan A. Nor...
Most research in learning for planning has concentrated on efficiency gains. Another important goal is improving the quality of final plans. Learning to improve plan quality has b...
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
In this paper we study the problem of computing an upward straight-line embedding of a directed graph G into a point set S, i.e. a planar drawing of G such that each vertex is map...
Carla Binucci, Emilio Di Giacomo, Walter Didimo, A...