受强制性开放获取政策约束的文章 - Emmanouil-Vasileios Vlatakis-Gkaragkounis了解详情
可在其他位置公开访问的文章：15 篇
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
强制性开放获取政策： US National Science Foundation, European Commission, Agence Nationale de la …
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
强制性开放获取政策： US National Science Foundation
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
强制性开放获取政策： US National Science Foundation, European Commission, Agence Nationale de la …
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
强制性开放获取政策： US National Science Foundation
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
强制性开放获取政策： US National Science Foundation
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
强制性开放获取政策： US National Science Foundation, European Commission, Agence Nationale de la …
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
强制性开放获取政策： US National Science Foundation
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
强制性开放获取政策： US National Science Foundation
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
强制性开放获取政策： US National Science Foundation, A*Star, Singapore, National Research …
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
强制性开放获取政策： US National Science Foundation, US Department of Defense, Agence Nationale …
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
强制性开放获取政策： US National Science Foundation, US Department of Defense
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
强制性开放获取政策： US National Science Foundation, US National Aeronautics and Space Administration
Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
I Sakos, EV Vlatakis-Gkaragkounis, P Mertikopoulos, G Piliouras
Advances in Neural Information Processing Systems 36, 2024
强制性开放获取政策： A*Star, Singapore, Agence Nationale de la Recherche, National Research …
Smoothed Complexity of SWAP in Local Graph Partitioning
X Chen, C Guo, EV Vlatakis-Gkaragkounis, M Yannakakis
Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024
强制性开放获取政策： US National Science Foundation
Reconstructing weighted voting schemes from partial information about their power indices
H Bennett, A De, R Servedio, EV Vlatakis-Gkaragkounis
Conference on Learning Theory, 500-565, 2021
强制性开放获取政策： US National Science Foundation
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