2 citations · 2 across the 4 of their papers we have counts for
6 papers
Curvature-Dependent Lower Bounds for Frank-Wolfe
Jannis Halbey, Christophe Roux, Sebastian Pokutta
The Frank-Wolfe algorithm achieves a convergence rate of for smooth convex optimization over compact convex domains, accelerating to when bo…
Lower Bounds for Frank-Wolfe on Strongly Convex Sets
Jannis Halbey, Daniel Deza, Max Zimmer +3
We present a constructive lower bound of for Frank-Wolfe (FW) when both the objective and the constraint set are smooth and strongly convex, showing that…
A Unified Toolbox for Multipartite Entanglement Certification
Ye-Chao Liu, Jannis Halbey, Sebastian Pokutta +1
We present a unified framework for multipartite entanglement characterization based on the conditional gradient (CG) method, incorporating both fast heuristic detection and rigorou…
Efficient Quadratic Corrections for Frank-Wolfe Algorithms
Jannis Halbey, Seta Rakotomandimby, Mathieu Besançon +2
We develop a Frank-Wolfe algorithm with corrective steps, generalizing previous algorithms including blended conditional gradients, blended pairwise conditional gradients, and full…
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…
Flexible block-iterative analysis for the Frank-Wolfe algorithm
Gábor Braun, Jannis Halbey, Sebastian Pokutta +1
We prove that the block-coordinate Frank-Wolfe (BCFW) algorithm converges with state-of-the-art rates in both convex and nonconvex settings under a very mild "block-iterative" assu…