We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. 'similar' point pairs. We define the similarity in informa...
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
This paper proposes a novel approach to measuring XML document similarity by taking into account the semantics between XML elements. The motivation of the proposed approach is to ...
—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...