We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...
Our system for the Novelty Track at TREC 2004 looks beyond sentence boundaries as well as within sentences to identify novel, nonduplicative passages. It tries to identify text sp...
Semi-supervised clustering allows a user to specify available prior knowledge about the data to improve the clustering performance. A common way to express this information is in ...
Several clustering algorithms equipped with pairwise hard constraints between data points are known to improve the accuracy of clustering solutions. We develop a new clustering alg...
Martin H. C. Law, Alexander P. Topchy, Anil K. Jai...
We propose consensus propagation, an asynchronous distributed protocol for averaging numbers across a network. We establish convergence, characterize the convergence rate for regul...