Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...
We examine the analysis of hyperspectral data produced by the Hyperspectral Core Imager of AngloGold Ashanti. The dimension of the data is reduced using diffusion maps and the dat...
This paper presents a modified K-means algorithm that can be used for removing noise in multicolor motion capture image sequences. These images have been produced using the Illumi...