Most clustering algorithms operate by optimizing (either implicitly or explicitly) a single measure of cluster solution quality. Such methods may perform well on some data sets bu...
Subspace clustering is an extension of traditional clustering that seeks to find clusters in different subspaces within a dataset. This is a particularly important challenge with...
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
Using off-the-shelf commodity workstations to build a cluster for parallel computing has become a common practice. In studying or designing a cluster of workstations one should ha...
To allow efficient browsing of large image collections, we have to provide a summary of its visual content. We present in this paper a robust approach to organize image databases:...