Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
: In this article, we propose an efficient and effective method for finding arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set o...
We study the online clustering problem where data items arrive in an online fashion. The algorithm maintains a clustering of data items into similarity classes. Upon arrival of v, ...
In this work we study the problem of Bipartite Correlation Clustering (BCC), a natural bipartite counterpart of the well studied Correlation Clustering (CC) problem. Given a bipart...
Nir Ailon, Noa Avigdor-Elgrabli, Edo Liberty, Anke...