In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
Given A := {a1, . . . , am} Rn, we consider the problem of reducing the input set for the computation of the minimum enclosing ball of A. In this note, given an approximate soluti...
Abstract. We give a (ln n + 1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . ....
We show that the length of the minimum weight Steiner triangulation (MWST) of a point set can be approximated within a constant factor by a triangulation algorithm based on quadtr...
The Chord algorithm is a popular, simple method for the succinct approximation of curves, which is widely used, under different names, in a variety of areas, such as, multiobjecti...