Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the...
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
The order and arrangement of dimensions (variates) is crucial for the effectiveness of a large number of visualization techniques such as parallel coordinates, scatterplots, recur...
—We introduce Zen, a new resource allocation framework that assigns application components to node clusters to achieve high availability for partial-fault tolerant (PFT) applicat...