Abstract. Real life scheduling problems are solved by heuristics with parameters defined by experts, as usual. In this paper a new approach is proposed where the parameters of vari...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
In this paper we present a new peer-to-peer (P2P) middleware called CHEap Distributed ARchitecture (Chedar). Chedar is totally decentralized and can be used as a basis for P2P app...
Annemari Auvinen, Mikko Vapa, Matthieu Weber, Niko...
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...