Develops median-of-means based algorithms for Nash equilibrium seeking in stochastic games with heavy-tailed noise (finite δ-moment, 1<δ≤2), proving almost sure convergence and rate plus online bias correction.
An operator splitting approach for distributed generalized nash equilibria computation
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Median-of-Means for Nash Equilibrium Seeking in Heavy-Tailed Games
Develops median-of-means based algorithms for Nash equilibrium seeking in stochastic games with heavy-tailed noise (finite δ-moment, 1<δ≤2), proving almost sure convergence and rate plus online bias correction.