Duality of ellipsoidal approximations via semi-infinite programming Filiz G¨urtuna∗ March 9, 2008 Abstract In this work, we develop duality of the minimum volume circumscribed ellipsoid and the maximum volume inscribed ellipsoid problems. We present a unified treatment of both problems using convex semi–infinite programming. We establish the known duality relationship between the minimum volume circumscribed ellipsoid problem and the optimal experimental design problem in statistics. The duality results are obtained using convex duality for semi–infinite programming developed in a functional analysis setting. Key words. Inscribed ellipsoid, circumscribed ellipsoid, minimum volume, maximum vol- ume, duality, semi–infinite programming, optimality conditions, optimal experimental de- sign, D-optimal design, John ellipsoid, L¨owner ellipsoid. Duality of ellipsoidal approximations via semi-infinite programming AMS(MOS) subject classifications: primary: 90C34, 46B20, 90C30, 90C46, 65K10; secondary: 52A38, 52A20, 52A21, 22C05, 54H15. ∗Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, Mary- land 21250, USA. E-mail:
[email protected]. Research partially supported by the National Science Foundation under grant DMS–0411955. 0 1 Introduction Inner and outer approximations of complicated sets by simpler ones is a fundamental ap- proach in applied mathematics. In this context, ellipsoids are very useful objects with their remarkable properties such as simple representation, an associated convex quadratic func- tion, and invariance, that is, an affine transformation of an ellipsoid is an ellipsoid. Therefore, ellipsoidal approximations are easier to work with than polyhedral approximations and their invariance property can be a gain over the spherical approximations in some applications such as clustering. Different criteria can be used for the quality of an approximating ellipsoid, each leading to a different optimization problem.