We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
One of the most important and challenging questions in the area of clustering is how to choose the best-fitting algorithm and parameterization to obtain an optiml clustering for t...
Martin Hahmann, Peter Benjamin Volk, Frank Rosenth...