mlsanityData to 14 Oct 2026

Fast convergence of Frank-Wolfe algorithms on polytopes

arXiv 2406.18789 ↗First posted 26 Jun 2024math.OCcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 26 Jun 2024.

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