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Adrian Kulmburg

Publications and source records attributed to Adrian Kulmburg.

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The Generalized Matrix Norm Problem

We study the computability of the operator norm of a matrix with respect to norms induced by linear operators. Our findings reveal that this problem can be solved exactly in polynomial time in certain situations, and we discuss how it can be approximated in other cases. Along the way, we investigate the concept of push-forward and pull-back of seminorms, which leads us to uncover novel duality principles that come into play when optimizing over the unit ball of norms.

math.NA

Approximability of the Containment Problem for Zonotopes and Ellipsotopes

The zonotope containment problem, i.e., whether one zonotope is contained in another, is a central problem in control theory. Applications include detecting faults and robustifying controllers by computing invariant sets, and obtain fixed points in reachability analysis. Despite the inherent co-NP-hardness of this problem, an approximation algorithm developed by S. Sadraddini and R. Tedrake has gained widespread recognition for its swift execution and consistent reliability in practice. In our study, we substantiate the precision of the algorithm with a definitive proof, elucidating the empirical accuracy observed in practice. Our proof hinges on establishing a connection between the containment problem and the computation of matrix norms, thereby enabling the extension of the approximation algorithm to encompass ellipsotopes -- a broader class of sets derived from zonotopes. We also explore the computational complexity of the ellipsotope containment problem with a focus on approximability. Finally, we present new methods to compute safe sets for linear dynamical systems, demonstrating the practical relevance of approximating the ellipsotope containment problem.

math.OC