The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Clustered microarchitectures are an effective organization to deal with the problem of wire delays and complexity by partitioning some of the processor resources. The organization ...
Clustering, or unsupervised classification, has many uses in fields that depend on grouping results from large amount of data, an example being the N-body cosmological simulation ...
Abstract. The definition of a community in social networks varies with applications. To generalize different types of communities, the concept of linkpattern based community was pr...
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...