In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to cre...
Anders Brun, Hans Knutsson, Hae-Jeong Park, Martha...
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,...
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
We develop a method for clustering all types of belief functions, in particular non-consonant belief functions. Such clustering is done when the belief functions concern multiple ...