collaborators

7 papers

math.OC2025

Linear Convergence of the Frank-Wolfe Algorithm over Product Polytopes

Gabriele Iommazzo, David Martínez-Rubio, Francisco Criado +2

We study the linear convergence of Frank-Wolfe algorithms over product polytopes. We analyze two condition numbers for the product polytope, namely the \emph{pyramidal width} and t…

math.OC2025

Improved algorithms and novel applications of the FrankWolfe.jl library

Mathieu Besançon, Sébastien Designolle, Jannis Halbey +6

Frank-Wolfe (FW) algorithms have emerged as an essential class of methods for constrained optimization, especially on large-scale problems. In this paper, we summarize the algorith…

math.OC2025

The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control

Elias Wirth, Mathieu Besançon, Sebastian Pokutta

We propose the pivoting meta algorithm (PM) to enhance optimization algorithms that generate iterates as convex combinations of vertices of a feasible region $C\subseteq \mathbb{R}…

cs.LG2025

Approximating Latent Manifolds in Neural Networks via Vanishing Ideals

Nico Pelleriti, Max Zimmer, Elias Wirth +1

Deep neural networks have reshaped modern machine learning by learning powerful latent representations that often align with the manifold hypothesis: high-dimensional data lie on l…

math.OC2025

Fast convergence of Frank-Wolfe algorithms on polytopes

Elias Wirth, Javier Pena, Sebastian Pokutta

We provide a template to derive convergence rates for the following popular versions of the Frank-Wolfe algorithm on polytopes: vanilla Frank-Wolfe, Frank-Wolfe with away steps, Fr…

math.OC2025

Adaptive Open-Loop Step-Sizes for Accelerated Convergence Rates of the Frank-Wolfe Algorithm

Elias Wirth, Javier Peña, Sebastian Pokutta

Recent work has shown that in certain settings, the Frank-Wolfe algorithm (FW) with open-loop step-sizes for a fixed parameter $\ell \in \mathbb{N},\,…