No-regret learning and mixed nash equilibria: They do not mix EV Vlatakis-Gkaragkounis, L Flokas, T Lianeas, P Mertikopoulos, ... Advances in Neural Information Processing Systems 33, 1380-1391, 2020 | 79* | 2020 |
Poincaré recurrence, cycles and spurious equilibria in gradient-descent-ascent for non-convex non-concave zero-sum games EV Vlatakis-Gkaragkounis, L Flokas, G Piliouras Advances in Neural Information Processing Systems 32, 2019 | 62 | 2019 |
Survival of the strictest: Stable and unstable equilibria under regularized learning with partial information A Giannou, EV Vlatakis-Gkaragkounis, P Mertikopoulos Conference on Learning Theory, 2147-2148, 2021 | 34 | 2021 |
Efficiently avoiding saddle points with zero order methods: No gradients required EV Vlatakis-Gkaragkounis, L Flokas, G Piliouras Advances in neural information processing systems 32, 2019 | 34* | 2019 |
On the approximation power of two-layer networks of random relus D Hsu, CH Sanford, R Servedio, EV Vlatakis-Gkaragkounis Conference on Learning Theory, 2423-2461, 2021 | 29 | 2021 |
On the rate of convergence of regularized learning in games: From bandits and uncertainty to optimism and beyond A Giannou, EV Vlatakis-Gkaragkounis, P Mertikopoulos Advances in Neural Information Processing Systems 34, 22655-22666, 2021 | 25 | 2021 |
Optimal private median estimation under minimal distributional assumptions C Tzamos, EV Vlatakis-Gkaragkounis, I Zadik Advances in Neural Information Processing Systems 33, 3301-3311, 2020 | 23 | 2020 |
Smoothed complexity of local Max-Cut and binary Max-CSP X Chen, C Guo, EV Vlatakis-Gkaragkounis, M Yannakakis, X Zhang Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing …, 2020 | 22 | 2020 |
Solving min-max optimization with hidden structure via gradient descent ascent EV Vlatakis-Gkaragkounis, L Flokas, G Piliouras Advances in Neural Information Processing Systems 34, 2373-2386, 2021 | 19 | 2021 |
First-order algorithms for min-max optimization in geodesic metric spaces M Jordan, T Lin, EV Vlatakis-Gkaragkounis Advances in Neural Information Processing Systems 35, 6557-6574, 2022 | 16 | 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 | 16 | 2022 |
On the convergence of policy gradient methods to Nash equilibria in general stochastic games A Giannou, K Lotidis, P Mertikopoulos, EV Vlatakis-Gkaragkounis Advances in Neural Information Processing Systems 35, 7128-7141, 2022 | 15 | 2022 |
Contracting with a learning agent G Guruganesh, Y Kolumbus, J Schneider, I Talgam-Cohen, ... arXiv preprint arXiv:2401.16198, 2024 | 14 | 2024 |
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 | 10 | 2023 |
The computational complexity of multi-player concave games and Kakutani fixed points CH Papadimitriou, EV Vlatakis-Gkaragkounis, M Zampetakis arXiv preprint arXiv:2207.07557, 2022 | 8 | 2022 |
Near-optimal statistical query lower bounds for agnostically learning intersections of halfspaces with gaussian marginals DJ Hsu, CH Sanford, R Servedio, EV Vlatakis-Gkaragkounis Conference on Learning Theory, 283-312, 2022 | 7 | 2022 |
Towards convergence to Nash equilibria in two-team zero-sum games F Kalogiannis, I Panageas, EV Vlatakis-Gkaragkounis arXiv preprint arXiv:2111.04178, 2021 | 4 | 2021 |
Teamwork makes von neumann work: Min-max optimization in two-team zero-sum games F Kalogiannis, I Panageas, EV Vlatakis-Gkaragkounis | 4 | 2021 |
Pattern search multidimensional scaling G Paraskevopoulos, E Tzinis, EV Vlatakis-Gkaragkounis, A Potamianos arXiv preprint arXiv:1806.00416, 2018 | 4 | 2018 |
Stochastic methods in variational inequalities: Ergodicity, bias and refinements EV Vlatakis-Gkaragkounis, A Giannou, Y Chen, Q Xie International Conference on Artificial Intelligence and Statistics, 4123-4131, 2024 | 3 | 2024 |