K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...
— This paper describes an approach to cooperative localization which finds its roots in robust estimation, employing an unknown-but-bounded error model for sensor measurements. ...
We introduce a new method for nding several types of optimal k-point sets, minimizing perimeter, diameter, circumradius, and related measures, by testing sets of the O(k) nearest ...
In this paper, we first provide a joint source and channel coding (JSCC) approach in estimating Gaussian sources over Gaussian MAC channels, as well as its sufficient and necessary...
Shuangqing Wei, Rajgopal Kannan, S. Sitharama Iyen...
The Voronoi diagram of a point set is a fundamental geometric structure that partitions the space into elementary regions of influence defining a discrete proximity graph and dual...
Jean-Daniel Boissonnat, Frank Nielsen, Richard Noc...