In this paper, we investigate the maximization of the amount of gathered data in a clustered wireless sensor network (WSN). The amount of gathered data is maximized by (1) choosing...
We study the problem of clustering uncertain objects whose locations are uncertain and described by probability density functions. We analyze existing pruning algorithms and experi...
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
This paper describes a method for proving termination of to logic programs based on abstract interpretation. The method ry-mapping pairs to abstract the relation between calls in t...
Naomi Lindenstrauss, Yehoshua Sagiv, Alexander Ser...
We propose a variational bayes approach to the problem of robust estimation of gaussian mixtures from noisy input data. The proposed algorithm explicitly takes into account the un...