Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Most clustering algorithms in fMRI analysis implicitly require some nontrivial assumption on data structure. Due to arbitrary distribution of fMRI time series in the temporal doma...
Clustering (or partitioning) is a crucial step between logic synthesis and physical design in the layout of a large scale design. A design verified at the logic synthesis level m...
The advent of service-oriented Grid computing has resulted in the need for Grid resources such as clusters to enforce user-specific service needs and expectations. Service Level ...
This paper proposes a clustering approach that explores both the content and the structure of XML documents for determining similarity among them. Assuming that the content and th...