This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional ...
Elth Ogston, Benno J. Overeinder, Maarten van Stee...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
— We present a new linear time technique to compute criticality information in a timing graph by dividing it into “zones”. Errors in using tightness probabilities for critica...
Hushrav Mogal, Haifeng Qian, Sachin S. Sapatnekar,...
—Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore ...
In this paper, we particularly focused our attention on how to enhance expressivity of ontologies when used as organized space values in a catalogue request process. Using the Wis...