Research map / Optimization / Nonconvex and smooth optimization
Stochastic No-regret Learning for General Games with Variance Reduction
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Closest papers by meaning
- Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games (NeurIPS 2022 · similarity 0.93)
- Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games (ICML 2018 · similarity 0.92)
- Local and Adaptive Mirror Descents in Extensive-Form Games (NeurIPS 2024 · similarity 0.90)
- Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback (NeurIPS 2025 · similarity 0.89)
- Optimism Without Regularization: Constant Regret in Zero-Sum Games (NeurIPS 2025 · similarity 0.88)
- Adaptively Perturbed Mirror Descent for Learning in Games (ICML 2024 · similarity 0.88)
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