This paper defines and discusses a new problem in the area of subspace clustering. It defines the problem of mining closed subspace clusters. This new concept allows for the culli...
Forming consensus clusters from multiple input clusterings can improve accuracy and robustness. Current clustering ensemble methods require specifying the number of consensus clust...
Pu Wang, Carlotta Domeniconi, Kathryn Blackmond La...
Large clusters of mutual dependence can cause problems for comprehension, testing and maintenance. This paper introduces the concept of coherent dependence clusters, techniques fo...
Syed S. Islam, Jens Krinke, David Binkley, Mark Ha...
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...