Many clustering algorithms only find one clustering solution. However, data can often be grouped and interpreted in many different ways. This is particularly true in the high-dim...
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
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...
We introduce two appearance-based methods for clustering a set of images of 3-D objects, acquired under varying illumination conditions, into disjoint subsets corresponding to ind...