The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to characterizing ...
We study the problem of mapping the N nodes of a complete t-ary tree on M memory modules so that they can be accessed in parallel by templates, i.e. distinct sets of nodes. Typica...
Vincenzo Auletta, Sajal K. Das, Amelia De Vivo, Ma...
Abstract. Hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. In many cases, annotation information for som...
Saket Navlakha, James Robert White, Niranjan Nagar...
We propose a novel clustering algorithm that is similar in spirit to classification trees. The data is recursively split using a criterion that applies a discrete curve evolution...
Longin Jan Latecki, Rajagopal Venugopal, Marc Sobe...