Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Sampling is a widely used technique to increase efficiency in database and data mining applications operating on large dataset. In this paper we present a scalable sampling imple...
We consider the use of a cluster of PC servers for Application Service Providers where applications and databases must remain autonomous. We use data replication to improve data av...
In this paper, an analysis of locally linear embedding (LLE) in the context of clustering is developed. As LLE conserves the local affine coordinates of points, shape protrusions ...
Fabio Cuzzolin, Diana Mateus, David Knossow, Edmon...
A key issue in supervised protein classification is the representation of input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-t...
Jason Weston, Christina S. Leslie, Eugene Ie, Deng...