16 citations · 19 across the 12 of their papers we have counts for
5 papers · 1 filter
A modified Riemannian Levenberg-Marquardt Algorithm for robust or constraint optimization on manifolds
Mateusz Baran, Ronny Bergmann
We extend the Levenberg-Marquardt method on Riemannian manifolds to a robust variant that allows to tackle problems from applications where outliers are to be expected. We formally…
A Riemannian quasi-Newton algorithm for optimization with Euclidean bounds
Mateusz Baran, Ronny Bergmann, Patryk Przybysz
We propose a Riemannian limited-memory BFGS method for optimization problems with Euclidean bounds. The method combines a limited-memory quasi-Newton update in the tangent space wi…
The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization
Ronny Bergmann, Hajg Jasa, Paula John +1
We consider a class of (possibly strongly) geodesically convex optimization problems on Hadamard manifolds, where the objective function splits into the sum of a smooth and a possi…
The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization
Ronny Bergmann, Hajg Jasa, Paula John +1
We consider the proximal gradient method on Riemannian manifolds for functions that are possibly not geodesically convex. Starting from the forward-backward-splitting, we define an…
The Riemannian Convex Bundle Method
Ronny Bergmann, Roland Herzog, Hajg Jasa
We introduce the convex bundle method to solve convex, non-smooth optimization problems on Riemannian manifolds of bounded sectional curvature. Each step of our method is based on…