Fast convergence of Frank-Wolfe algorithms on polytopes
Optimization and Control
2025-05-21 v4
Abstract
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, Frank-Wolfe with blended pairwise steps, and Frank-Wolfe with in-face directions. Our template shows how the convergence rates follow from two affine-invariant properties of the problem, namely, error bound and extended curvature. These properties depend solely on the polytope and objective function but not on any affine-dependent object like norms. For each one of the above algorithms, we derive rates of convergence ranging from sublinear to linear depending on the degree of the error bound.
Cite
@article{arxiv.2406.18789,
title = {Fast convergence of Frank-Wolfe algorithms on polytopes},
author = {Elias Wirth and Javier Pena and Sebastian Pokutta},
journal= {arXiv preprint arXiv:2406.18789},
year = {2025}
}
Comments
29 pages, 6 figures