In this paper, we propose a method which enables us to construct almost optimal broadcast schemes on an n-dimensional hypercube in the circuit switched, -port model. In this mode...
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
We study the expected number of interior vertices of degree i in a triangulation of a point set S, drawn uniformly at random from the set of all triangulations of S, and derive va...
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Abstract. Classical list scheduling is a very popular and efficient technique for scheduling jobs in parallel platforms. However, with the increasing number of processors, the cost...
Marc Tchiboukdjian, Nicolas Gast, Denis Trystram, ...