Orateur
Marco Sutti
(University of Geneva)
Description
Several applications in optimization, image and signal processing deal with
data that belong to the Stiefel manifold St(n, p), that is, the set of n × p
matrices with orthonormal columns. Some applications, for example, the
computation of the Karcher mean, require evaluating the geodesic distance
between two arbitrary points on St(n, p). This can be done by explicitly
constructing the geodesic connecting these two points. An existing method for
finding geodesics is the leapfrog algorithm introduced by J. L. Noakes, which
enjoys global convergence properties. We reinterpret this algorithm as a
nonlinear block Gauss-Seidel process and propose a new convergence proof based
on this framework for the case of St(n, p).
Co-auteur
Bart Vandereycken
