Content tagged with preprint

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• [W9] Learning in quantum games
• [W8] On the rate of convergence of Bregman proximal methods in constrained variational inequalities
• [W7] Explicit second-order min-max optimization methods with optimal convergence guarantees
• [W6] A unified stochastic approximation framework for learning in games
• [W5] Quick or cheap? Breaking points in dynamic markets
• [W4] Multi-agent online learning with imperfect information
• [W3] Online convex optimization and no-regret learning: Algorithms, guarantees and applications
• [W2] Boltzmann meets Nash: Energy-efficient routing in optical networks under uncertainty
• [W1] Power control via online learning in non-stationary MIMO networks