4 citations · 7 across the 19 of their papers we have counts for
4 papers · 2 filters
Strong Convexity of Sets in Riemannian Manifolds
Damien Scieur, David Martínez-Rubio, Thomas Kerdreux +2
Curvature properties of convex objects, such as strong convexity, are important in designing and analyzing convex optimization algorithms in the Hilbertian or Riemannian settings.…
Open Problem: Polynomial linearly-convergent method for geodesically convex optimization?
Christopher Criscitiello, David Martínez-Rubio, Nicolas Boumal
Let be a Lipschitz and geodesically convex function defined on a -dimensional Riemannian manifold . Does there exist a first-o…
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties
David Martínez-Rubio, Christophe Roux, Christopher Criscitiello +1
In this work, we study optimization problems of the form , where is defined on a product Riemannian manifold and i…
Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond
David Martínez-Rubio, Elias Wirth, Sebastian Pokutta
It has recently been shown that ISTA, an unaccelerated optimization method, presents sparse updates for the -regularized personalized PageRank problem, leading to cheap ite…