Mirror descent algorithms with productive/non-productive step switching achieve optimal convergence rates for bounded monotone operators and Lipschitz convex functional constraints in variational inequalities.
I., Lin, T., Zampetakis, M.: First-order algorithms for nonlinear gener- alized Nash equilibrium problems
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Mirror Descent-Type Algorithms for the Variational Inequality Problem with Functional Constraints
Mirror descent algorithms with productive/non-productive step switching achieve optimal convergence rates for bounded monotone operators and Lipschitz convex functional constraints in variational inequalities.