Mirror Descent-Ascent for mean-field min-max problems

ArXi:2402.08106v3 Announce Type: replace-cross We study two variants of the mirror descent-ascent (MDA) algorithm for solving min-max problems on the space of measures: simultaneous and alternating. We work under assumptions of convexity-concavity and relative smoothness of the payoff function with respect to a suitable Bregman divergence, defined on the space of measures via flat derivatives.