Riemannian Optimization for Non-convex Euclidean Distance Geometry with
Global Recovery Guarantees
Riemannian Optimization for Non-convex Euclidean Distance Geometry with
Global Recovery Guarantees
The problem of determining the configuration of points from partial distance information, known as the Euclidean Distance Geometry (EDG) problem, is fundamental to many tasks in the applied sciences. In this paper, we propose two algorithms grounded in the Riemannian optimization framework to address the EDG problem. Our approach formulates …