Data is often collected over a distributed network, but in many cases, is so voluminous that it is impractical and undesirable to collect it in a central location. Instead, we mus...
Writing parallel applications for computational grids is a challenging task. To achieve good performance, algorithms designed for local area networks must be adapted to the differ...
Thilo Kielmann, Rutger F. H. Hofman, Henri E. Bal,...
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...
In this paper we study the constrained consensus problem, i.e. the problem of reaching a common point from the estimates generated by multiple agents that are constrained to lie in...
Abstract--This paper proposes a new algorithm for the reduction of the number of colors in an image. The proposed adaptive color reduction (ACR) technique achieves color reduction ...