We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every b...
We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...