paper

Last-Iterate Convergence of Frank--Wolfe for Nonlinear Variational Inequalities on Polytopes

arXiv:2610.17127

Abstract

We consider the Frank--Wolfe algorithm for solving variational inequalities over compact polytopes under a monotone operator . The linear minimization oracle returns vertices, and we assume a coercivity condition on the Jacobian of at a solution. We prove last-iterate convergence to the unique solution at rate for step sizes with . The bound holds uniformly over starting points and vertex tie-breaking. In particular, both and give distance. A matching lower bound shows that this distance guarantee is worst-case order-optimal among prescribed admissible step-size schedules. We also obtain rates for the Frank--Wolfe gap and for the dual gap. These yield and calls to each oracle for sustained gap accuracy when and , respectively, with instance-dependent constants. We also treat more general prescribed step-size schedules.

arXiv comment30 pages, 4 figures