The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Median-shift is a mode seeking algorithm that relies on
computing the median of local neighborhoods, instead of
the mean. We further combine median-shift with Locality
Sensitive...
A fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. Often, homologies between po...
Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Heinz...
—We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and ac...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...