editors, Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pages 391-401, 2019.
[10] Tatjana Chavdarova, Matteo Pagliardini, Sebastian U. Stich, François Fleuret, and Martin Jaggi. Taming gans with lookahead-minmax. In 9th International Conference on Learning Representations, ICLR 2021. OpenReview.net, 2021.
[11] Steve Chien and Alistair Sinclair. Convergence to approximate nash equilibria in congestion games. In Nikhil Bansal, Kirk Pruhs, and Clifford Stein, editors, Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2007, New Orleans, Louisiana, USA, January 7-9, 2007, pages 169-178. SIAM, 2007.
[12] Ashok Cutkosky and Francesco Orabona. Black-box reductions for parameter-free online learning in banach spaces. In Conference On Learning Theory, pages 1493-1529. PMLR, 2018.
[13] Constantinos Daskalakis, Alan Deckelbaum, and Anthony Kim. Near-optimal no-regret algorithms for zero-sum games. In Dana Randall, editor, Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2011, pages 235–254. SIAM, 2011.
[14] Constantinos Daskalakis, Maxwell Fishelson, and Noah Golowich. Near-optimal no-regret learning in general games. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, pages 27604-27616, 2021.
[15] Ofer Dekel, Arthur Flajolet, Nika Haghtalab, and Patrick Jaillet. Online learning with a hint. In Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett, editors, Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, pages 5299-5308, 2017.
[16] John C. Duchi, Elad Hazan, and Yoram Singer. Adaptive subgradient methods for online learning and stochastic optimization. In Adam Tauman Kalai and Mehryar Mohri, editors, COLT 2010 - The 23rd Conference on Learning Theory, Haifa, Israel, June 27-29, 2010, pages 257-269. Omnipress, 2010.
[17] Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, and Yishay Mansour. Regret minimization and convergence to equilibria in general-sum markov games. CoRR, abs/2207.14211, 2022.
[18] Gabriele Farina and Tuomas Sandholm. Model-free online learning in unknown sequential decision making problems and games. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021.
[19] Gabriele Farina, Robin Schmucker, and Tuomas Sandholm. Bandit linear optimization for sequential decision making and extensive-form games. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021.
[20] Yoav Freund and Robert E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci., 55(1):119-139, 1997.
[21] Gauthier Gidel, Hugo Berard, Gaetan Vignoud, Pascal Vincent, and Simon Lacoste-Julien. A variational inequality perspective on generative adversarial networks. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019. OpenReview.net, 2019.
[22] Denizalp Goktas, Jiayi Zhao, and Amy Greenwald. Robust no-regret learning in min-max stackelberg games. In 21st International Conference on Autonomous Agents and Multiagents Systems, AAMAS 2022.
[23] Elad Hazan. Introduction to online convex optimization. Found. Trends Optim., 2(3-4):157-325, 2016.