We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
In this paper, we will look at substructure clustering of sequential 3d objects. A sequential 3d object is a set of points located in a three dimensional space that are linked up ...
Graph clustering has become ubiquitous in the study of relational data sets. We examine two simple algorithms: a new graphical adaptation of the k-medoids algorithm and the Girvan...
Overlapping genes (encoded on the same DNA strand but in different frames) are thought to be rare and, therefore, were largely neglected in the past. In a test set of 800 viruses ...
This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...