This paper investigates the design of parallel algorithmic strategies that address the efficient use of both, memory hierarchies within each processor and a multilevel clustered ...
Frank K. H. A. Dehne, Stefano Mardegan, Andrea Pie...
This paper presents an innovative hierarchical feedback adaptation method that efficiently controls the dynamic QoS behavior of real-time distributed data-flow applications, such ...
A distributed memory parallel version of the group average Hierarchical Agglomerative Clustering algorithm is proposed to enable scaling the document clustering problem to large c...
Rebecca Cathey, Eric C. Jensen, Steven M. Beitzel,...
Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the d...
Manoranjan Dash, Simona Petrutiu, Peter Scheuerman...
Clustering of data has numerous applications and has been studied extensively. It is very important in Bioinformatics and data mining. Though many parallel algorithms have been des...