We consider the following clustering problem: we have a complete graph on n vertices
(items), where each edge (u, v) is labeled either+ or− depending on whether u and v have …

We continue the investigation of problems concerning correlation clustering or clustering
with qualitative information, which is a clustering formulation that has been studied recently …

We consider the following general correlation-clustering problem [1]: given a graph with real
edge weights (both positive and negative), partition the vertices into clusters to minimize the …

We solve several open problems concerning the correlation clustering problem introduced
by Bansal, Blum and Chawla [1]. We give an equivalence argument between these …

We study a novel clustering problem in which the pairwise relations between objects are
categorical. This problem can be viewed as clustering the vertices of a graph whose edges …

We consider the following general correlation-clustering problem [N. Bansal, A. Blum, S.
Chawla, Correlation clustering, in: Proc. 43rd Annu. IEEE Symp. on Foundations of …

Abstract We consider the Correlation Clustering problem introduced in [2]. Given a graph
G=(V, E) where each edge is labeled either “+”(similar) or “−”(different), we want to cluster …

Correlation clustering is a type of clustering that uses a basic form of input data: For every
pair of data items, the input specifies whether they are similar (belonging to the same …

We introduce a new approach for finding overlapping clusters given pairwise similarities of
objects. In particular, we relax the problem of correlation clustering by allowing an object to …

Correlation clustering is a central topic in unsupervised learning, with many applications in
ML and data mining. In correlation clustering, one receives as input a signed graph and the …