| 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 | 51 | 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 | 36 | 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 | 25 | 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 | 25* | 2022 |
| Meta-learning in games K Harris, I Anagnostides, G Farina, M Khodak, ZS Wu, T Sandholm arXiv preprint arXiv:2209.14110, 2022 | 16 | 2022 |
| 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 | 14 | 2022 |
| Efficiently computing nash equilibria in adversarial team markov games F Kalogiannis, I Anagnostides, I Panageas, EV Vlatakis-Gkaragkounis, ... arXiv preprint arXiv:2208.02204, 2022 | 12 | 2022 |
| Deterministic distributed algorithms and lower bounds in the hybrid model I Anagnostides, T Gouleakis arXiv preprint arXiv:2108.01740, 2021 | 11 | 2021 |
| Metric-distortion bounds under limited information I Anagnostides, D Fotakis, P Patsilinakos Journal of Artificial Intelligence Research 74, 1449-1483, 2022 | 10 | 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, 2024 | 9 | 2024 |
| Near-Optimal -Regret Learning in Extensive-Form Games I Anagnostides, G Farina, T Sandholm International Conference on Machine Learning, 814-839, 2023 | 7 | 2023 |
| 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 | 7* | 2021 |
| 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 | 6 | 2023 |
| 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, 2024 | 5 | 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 | 4 | 2022 |
| 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 | 4 | 2022 |
| Steering no-regret learners to optimal equilibria BH Zhang, G Farina, I Anagnostides, F Cacciamani, SM McAleer, ... arXiv preprint arXiv:2306.05221, 2023 | 3 | 2023 |
| Frequency-Domain Representation of First-Order Methods: A Simple and Robust Framework of Analysis∗ I Anagnostides, I Panageas Symposium on Simplicity in Algorithms (SOSA), 131-160, 2022 | 3 | 2022 |
| Solving zero-sum games through alternating projections I Anagnostides, P Penna arXiv preprint arXiv:2010.00109, 2020 | 2 | 2020 |
| Asymptotically optimal communication in simple mechanisms I Anagnostides, D Fotakis, P Patsilinakos International Symposium on Algorithmic Game Theory, 17-31, 2020 | 2 | 2020 |
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
