forward-backward splitting 1manifold algorithms 1nonconvex optimization 1proximal gradient method 1riemannian optimization 1
From the 1 of 3 linked papers with an AI index.
3 papers
math.OC2026
The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization
Ronny Bergmann, Hajg Jasa, Paula John +1
The paper proposes an intrinsic Riemannian proximal gradient algorithm that operates directly on manifolds without requiring an embedding, and analyzes its convergence for possibly…
math.OC2026
Optimization on Weak Riemannian Manifolds
Valentina Zalbertus, Max Pfeffer, Alexander Schmeding
Riemannian structures on infinite-dimensional manifolds arise naturally in shape analysis and shape optimization. These applications lead to optimization problems on manifolds whic…
math.OC2025
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…