?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and support-vector clustering. Like the latter, it associates every data poin...
In the present paper we explain the basic ideas of Robust Perron Cluster Analysis (PCCA+) and exemplify the different application areas of this new and powerful method. Recently, ...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
—A novel method CLOSS intended for textual databases is proposed. It successfully identifies misspelled string clusters, even if the cluster border is not prominent. The method ...