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...
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
We present a clustering scheme that combines a mode-seeking phase with a cluster merging phase in the corresponding density map. While mode detection is done by a standard graph-b...
—Previous studies have demonstrated that document clustering performance can be improved significantly in lower dimensional linear subspaces. Recently, matrix factorization base...
Abstract. This paper addresses the problem of clustering images of objects seen from different viewpoints. That is, given an unlabelled set of images of n objects, we seek an unsup...