Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
— Recent work has revealed a close connection between certain information theoretic divergence measures and properties of Mercer kernel feature spaces. Specifically, it has been...
ct We introduce a new family of spectral partitioning methods. Edge separators of a graph are produced by iteratively reweighting the edges until the graph disconnects into the pre...
We address the problem of determining a natural local neighbourhood or "cluster" associated to a given seed vertex in an undirected graph. We formulate the task in terms...
Pekka Orponen, Satu Elisa Schaeffer, Vanesa Avalos...