4 citations · 7 across the 19 of their papers we have counts for
3 papers · 1 filter
Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization
Simon Vary, David Martínez-Rubio, Patrick Rebeschini
We study first-order algorithms that are uniformly stable for empirical risk minimization (ERM) problems that are convex and smooth with respect to -norms, . We propos…
Non-Euclidean High-Order Smooth Convex Optimization
Juan Pablo Contreras, Cristóbal Guzmán, David Martínez-Rubio
We develop algorithms for the optimization of convex objectives that have Hölder continuous -th derivatives by using a -th order oracle, for any . Our algorithms wo…
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point
David Martínez-Rubio, Christophe Roux, Sebastian Pokutta
In this work, we analyze two of the most fundamental algorithms in geodesically convex optimization: Riemannian gradient descent and (possibly inexact) Riemannian proximal point. W…