This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
Abstract. With many organizations now employing multiple data centres around the world to share global traffic load, it is important to understand the effects of geographical distr...
The decentralized process of configuring enterprise applications is complex and error-prone, involving multiple participants/roles and numerous configuration changes across multipl...
Jules White, Douglas C. Schmidt, Krzysztof Czarnec...
Dynamically allocating computing nodes to parallel applications is a promising technique for improving the utilization of cluster resources. We introduce the concept of dynamic ef...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...