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
73 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
44 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
41 * 2022 Uncoupled Learning Dynamics with I Anagnostides, G Farina, C Kroer, CW Lee, H Luo, T Sandholm
Advances in Neural Information Processing Systems 35, 3292-3304, 2022
34 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
21 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
21 2022 Meta-learning in games K Harris, I Anagnostides, G Farina, M Khodak, ZS Wu, T Sandholm
arXiv preprint arXiv:2209.14110, 2022
20 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
18 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 Steering no-regret learners to optimal equilibria BH Zhang, G Farina, I Anagnostides, F Cacciamani, SM McAleer, ...
15 * 2023 Near-Optimal I Anagnostides, G Farina, T Sandholm
International Conference on Machine Learning, 814-839, 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 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
13 2023 Deterministic distributed algorithms and lower bounds in the hybrid model I Anagnostides, T Gouleakis
arXiv preprint arXiv:2108.01740, 2021
13 2021 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 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
9 2022 Efficient BH Zhang, I Anagnostides, G Farina, T Sandholm
arXiv preprint arXiv:2402.09670, 2024
8 2024 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
7 2022 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 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
3 2024 
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon UniversityGeverifieerd e-mailadres voor cs.cmu.edu