Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also...
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...
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sou...