The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
In this paper, we present the current development progress of our dynamic insert strategy based on the Intelligent Cluster Index (ICIx), which is a new type of multidimensional da...
In this paper, we propose novel algorithms for total variation (TV) based image restoration and parameter estimation utilizing variational distribution approximations. Within the h...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
Abstract. Bayesian approaches to density estimation and clustering using mixture distributions allow the automatic determination of the number of components in the mixture. Previou...
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...