The k-means method is an old but popular clustering algorithm known for its observed speed and its simplicity. Until recently, however, no meaningful theoretical bounds were known...
Keyword search on data represented as graphs, is receiving lot of attention in recent years. Initial versions of keyword search systems assumed that the graph is memory resident. ...
Abstract We develop a distance metric for clustering and classification algorithms which is invariant to affine transformations and includes priors on the transformation parameters...
In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering...
Archana Venkataraman, Koene R. A. Van Dijk, Randy ...
Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF`s batch nature necessitates recomputation of whole basis set for new samples...