Emmanouil V. Vlatakis-Gkaragkounis

Orcid: 0009-0009-7549-538X

Affiliations:
  • University of California, Berkeley, Simons Institute for the Theory of Computing,, CA, USA
  • Columbia University, Computer Science Department, New York City, NY, USA (PhD 2022)


According to our database1, Emmanouil V. Vlatakis-Gkaragkounis authored at least 28 papers between 2018 and 2024.

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Bibliography

2024
Contracting with a Learning Agent.
CoRR, 2024

Smoothed Complexity of SWAP in Local Graph Partitioning.
Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games.
CoRR, 2023

Curvature-Independent Last-Iterate Convergence for Games on Riemannian Manifolds.
CoRR, 2023

Chaos persists in large-scale multi-agent learning despite adaptive learning rates.
CoRR, 2023

The Computational Complexity of Multi-player Concave Games and Kakutani Fixed Points.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Algorithms and Complexity for Computing Nash Equilibria in Adversarial Team Games.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Exploiting hidden structures in non-convex games for convergence to Nash equilibrium.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards convergence to Nash equilibria in two-team zero-sum games.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficiently Computing Nash Equilibria in Adversarial Team Markov Games.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Beyond Worst-Case Analysis of Optimization in the Era of Machine Learning
PhD thesis, 2022

First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the convergence of policy gradient methods to Nash equilibria in general stochastic games.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Near-Optimal Statistical Query Lower Bounds for Agnostically Learning Intersections of Halfspaces with Gaussian Marginals.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Teamwork makes von Neumann work: Min-Max Optimization in Two-Team Zero-Sum Games.
CoRR, 2021

From Learning with Partial Information to Bandits: Only Strict Nash Equilibria are Stable.
CoRR, 2021

Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The convergence rate of regularized learning in games: From bandits and uncertainty to optimism and beyond.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Approximation Power of Two-Layer Networks of Random ReLUs.
Proceedings of the Conference on Learning Theory, 2021

Survival of the strictest: Stable and unstable equilibria under regularized learning with partial information.
Proceedings of the Conference on Learning Theory, 2021

Reconstructing weighted voting schemes from partial information about their power indices.
Proceedings of the Conference on Learning Theory, 2021

2020
Smoothed complexity of local max-cut and binary max-CSP.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimal Private Median Estimation under Minimal Distributional Assumptions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficiently avoiding saddle points with zero order methods: No gradients required.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Pattern Search Multidimensional Scaling.
CoRR, 2018


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