Each clustering algorithm induces a similarity between given data points, according to the underlying clustering criteria. Given the large number of available clustering technique...
—This paper proposes a method of learning a similarity matrix from pairwise constraints for interactive clustering. The similarity matrix can be learned by solving an optimizatio...
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...
Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate them into traditional clustering methods, such as ...