Theoretical background is provided towards the mathematical foundation of the minimum
enclosing ball problem. This problem concerns the determination of the unique spherical …

The minimum volume ellipsoid (MVE) estimator is an important tool in robust regression and
outlier detection in statistics. We develop fast and efficient algorithms for the MVE estimator …

Generalizing the Fréchet mean from the Euclidean metric is not able to properly capture the
geometric characteristics of many non-trivial operations, such as the non-dot inner product …

In this paper, an algorithm is introduced that computes an arbitrarily fine approximation of
the smallest enclosing ball of a point set in any dimension. This operation is important in, for …

In this doctoral thesis, we study the problem of computing the ball of smallest radius
enclosing a given set of points in any number of dimensions. Variations of this problem arise …

In the world of big data, extracting meaningful insights from large and continually growing
distributed datasets is a major challenge. Classical clustering algorithms are effective at …

We propose an algorithm for computing the exact minimum enclosing ball of large point sets
in general dimensions. It aims to reduce the number of passes by retrieving a well-balanced …

We develop and analyse a first-order algorithm for the A-optimal experimental design
problem. The problem is first presented as a special case of a parametric family of optimal …

We consider the construction of the smallest ball B∗ enclosing a set X n formed by n points
in R d. We show that any probability measure on X n, with mean c and variance matrix V …

Abstract Support Vector Clustering (SVC) algorithm reformulates SVM's Quadratic
Programming as a minimum enclosing ball (MEB) problem, where every point in the data …