Abstract. Finite mixture models can be used in estimating complex, unknown probability distributions and also in clustering data. The parameters of the models form a complex repres...
Data-intensive parallel applications on clouds need to deploy large data sets from the cloud's storage facility to all compute nodes as fast as possible. Many multicast algori...
Tatsuhiro Chiba, Mathijs den Burger, Thilo Kielman...
When users' tasks in a distributed heterogeneous computing environment (e.g., cluster of heterogeneous computers) are allocated resources, the total demand placed on some sys...
Jong-Kook Kim, Debra A. Hensgen, Taylor Kidd, Howa...
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...