Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games I Anagnostides, C Daskalakis, G Farina, M Fishelson, N Golowich, ... Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 77 | 2022 |
On last-iterate convergence beyond zero-sum games I Anagnostides, I Panageas, G Farina, T Sandholm International Conference on Machine Learning, 536-581, 2022 | 47 | 2022 |
Near-optimal no-regret learning dynamics for general convex games G Farina, I Anagnostides, H Luo, CW Lee, C Kroer, T Sandholm Advances in Neural Information Processing Systems 35, 39076-39089, 2022 | 46* | 2022 |
Uncoupled Learning Dynamics with Swap Regret in Multiplayer Games I Anagnostides, G Farina, C Kroer, CW Lee, H Luo, T Sandholm Advances in Neural Information Processing Systems 35, 3292-3304, 2022 | 35 | 2022 |
On the convergence of no-regret learning dynamics in time-varying games I Anagnostides, I Panageas, G Farina, T Sandholm Advances in Neural Information Processing Systems 36, 16367-16405, 2023 | 23 | 2023 |
Efficiently computing nash equilibria in adversarial team markov games F Kalogiannis, I Anagnostides, I Panageas, EV Vlatakis-Gkaragkounis, ... arXiv preprint arXiv:2208.02204, 2022 | 22 | 2022 |
Meta-learning in games K Harris, I Anagnostides, G Farina, M Khodak, ZS Wu, T Sandholm arXiv preprint arXiv:2209.14110, 2022 | 21 | 2022 |
Computing optimal equilibria and mechanisms via learning in zero-sum extensive-form games B Zhang, G Farina, I Anagnostides, F Cacciamani, S McAleer, A Haupt, ... Advances in Neural Information Processing Systems 36, 2659-2699, 2023 | 20 | 2023 |
Steering no-regret learners to optimal equilibria BH Zhang, G Farina, I Anagnostides, F Cacciamani, SM McAleer, ... | 19* | 2023 |
Faster no-regret learning dynamics for extensive-form correlated and coarse correlated equilibria I Anagnostides, G Farina, C Kroer, A Celli, T Sandholm arXiv preprint arXiv:2202.05446, 2022 | 17 | 2022 |
Near-Optimal -Regret Learning in Extensive-Form Games I Anagnostides, G Farina, T Sandholm International Conference on Machine Learning, 814-839, 2023 | 14 | 2023 |
Algorithms and complexity for computing nash equilibria in adversarial team games I Anagnostides, F Kalogiannis, I Panageas, EV Vlatakis-Gkaragkounis, ... arXiv preprint arXiv:2301.02129, 2023 | 14 | 2023 |
Metric-distortion bounds under limited information I Anagnostides, D Fotakis, P Patsilinakos Journal of Artificial Intelligence Research 74, 1449-1483, 2022 | 14 | 2022 |
Deterministic distributed algorithms and lower bounds in the hybrid model I Anagnostides, T Gouleakis arXiv preprint arXiv:2108.01740, 2021 | 13 | 2021 |
Efficient -Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games B Zhang, I Anagnostides, G Farina, T Sandholm Advances in Neural Information Processing Systems 37, 125192-125230, 2024 | 11 | 2024 |
Optimistic mirror descent either converges to nash or to strong coarse correlated equilibria in bimatrix games I Anagnostides, G Farina, I Panageas, T Sandholm Advances in Neural Information Processing Systems 35, 16439-16454, 2022 | 10 | 2022 |
Almost Universally Optimal Distributed Laplacian Solvers via Low-Congestion Shortcuts I Anagnostides, C Lenzen, B Haeupler, G Zuzic, T Gouleakis https://arxiv.org/abs/2109.05151, 2021 | 10* | 2021 |
Dimensionality and coordination in voting: The distortion of STV I Anagnostides, D Fotakis, P Patsilinakos Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 4776-4784, 2022 | 8 | 2022 |
Optimistic policy gradient in multi-player markov games with a single controller: Convergence beyond the minty property I Anagnostides, I Panageas, G Farina, T Sandholm Proceedings of the AAAI Conference on Artificial Intelligence 38 (9), 9451-9459, 2024 | 4 | 2024 |
On the complexity of computing sparse equilibria and lower bounds for no-regret learning in games I Anagnostides, A Kalavasis, T Sandholm, M Zampetakis arXiv preprint arXiv:2311.14869, 2023 | 4 | 2023 |