Content tagged with 2021

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• [W5] A heuristic for estimating Nash equilibria in first-price auctions with correlated values
• [J34] Minibatch forward-backward-forward methods for solving stochastic variational inequalities
• [J33] Robust power management via learning and game design
• [C73] Fast routing under uncertainty: Adaptive learning in congestion games with exponential weights
• [C72] The convergence rate of regularized learning in games: From bandits and uncertainty to optimism and beyond
• [C71] Sifting through the noise: Universal first-order methods for stochastic variational inequalities
• [C70] Adaptive first-order methods revisited: Convex optimization without Lipschitz requirements
• [C69] Equilibrium tracking and convergence in dynamic games
• [C68] Optimization in open networks via dual averaging
• [C67] Adaptive learning in continuous games: Optimal regret bounds and convergence to Nash equilibrium
• [C66] Survival of the strictest: Stable and unstable equilibria under regularized learning with partial information
• [C65] The last-iterate convergence rate of optimistic mirror descent in stochastic variational inequalities
• [C64] The limits of min-max optimization algorithms: Convergence to spurious non-critical sets
• [C63] Zeroth-order non-convex learning via hierarchical dual averaging
• [C62] Regret minimization in stochastic non-convex learning via a proximal-gradient approach
• [C61] Adaptive extra-gradient methods for min-max optimization and games