Approximation of Riemannian Distances and Applications to Distance-Based Learning on Manifolds

Philipp Harms, Elodie Maignant, Stefan Schlager

Several important algorithms for machine learning and data analysis use pairwise distances as input. On Riemannian manifolds these distances may be prohibitively costly to compute,…