—Probability models are estimated by use of penalized log-likelihood criteria related to AIC and MDL. The accuracies of the density estimators are shown to be related to the trad...
Density estimation for observational data plays an integral role in a broad spectrum of applications, e.g. statistical data analysis and information-theoretic image registration. ...
In this paper, we make two contributions to the field of level set based image segmentation. Firstly, we propose shape dissimilarity measures on the space of level set functions wh...
Abstract. We examine efficacy of a classifier based on average of kernel density estimators; each estimator corresponds to a different data "resolution". Parameters of th...
Abstract. A new classification algorithm based on combination of kernel density estimators is introduced. The method combines the estimators with different bandwidths what can be i...