Frank-Wolfe iterates for monotone variational inequalities converge asymptotically to the solution set under vanishing nonsummable step sizes, with the gap vanishing and unique convergence in the strongly monotone case.
In: Proceedings of the 29th International Conference on Neural Information Processing Systems - Volume 1
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Convergence of the Frank-Wolfe Algorithm for Monotone Variational Inequalities
Frank-Wolfe iterates for monotone variational inequalities converge asymptotically to the solution set under vanishing nonsummable step sizes, with the gap vanishing and unique convergence in the strongly monotone case.