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50 results on '"Mertikopoulos, Panayotis"'

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1. Explicit second-order min-max optimization methods with optimal convergence guarantees

2. Minibatch Forward-Backward-Forward Methods for Solving Stochastic Variational Inequalities

3. AdaGrad avoids saddle points

4. UnderGrad: A universal black-box optimization method with almost dimension-free convergence rate guarantees

5. Nested bandits

6. The Dynamics of Riemannian Robbins-Monro Algorithms

7. Learning in games from a stochastic approximation viewpoint

8. Adaptive extra-gradient methods for min-max optimization and games

9. On the rate of convergence of Bregman proximal methods in constrained variational inequalities

10. On the convergence of policy gradient methods to Nash equilibria in general stochastic games

11. Survival of dominated strategies under imitation dynamics

12. Learning in Games with Quantized Payoff Observations

13. Fast routing under uncertainty: Adaptive learning in congestion games with exponential weights

14. Adaptive first-order methods revisited: Convex optimization without Lipschitz requirements

15. Sifting through the noise: Universal first-order methods for stochastic variational inequalities

16. The last-iterate convergence rate of optimistic mirror descent in stochastic variational inequalities

17. Survival of the strictest: Stable and unstable equilibria under regularized learning with partial information

18. A heuristic for estimating Nash equilibria in first-price auctions with correlated values

19. Online and Stochastic Optimization beyond Lipschitz Continuity: A Riemannian Approach

20. Zeroth-order non-convex learning via hierarchical dual averaging

21. Learning in nonatomic games, Part I: Finite action spaces and population games

22. Regret minimization in stochastic non-convex learning via a proximal-gradient approach

23. Equilibrium tracking and convergence in dynamic games

24. Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium

25. Optimization in Open Networks via Dual Averaging

26. No-regret learning and mixed Nash equilibria: They do not mix

27. An adaptive mirror-prox algorithm for variational inequalities with singular operators

28. Gradient-free Online Learning in Games with Delayed Rewards

29. Fast Gradient-Free Optimization in Distributed Multi-User MIMO Systems

30. Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling

31. The limits of min-max optimization algorithms: convergence to spurious non-critical sets

32. Online optimization and learning in games: Theory and applications

33. Forward-backward-forward methods with variance reduction for stochastic variational inequalities

34. On the Convergence of Single-Call Stochastic Extra-Gradient Methods

35. Cautious regret minimization: Online optimization with long-term budget constraints

36. On the convergence of stochastic forward-backward-forward algorithms with variance reduction in pseudo-monotone variational inequalities

37. Learning in Games with Lossy Feedback

38. Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

39. Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?

40. Stochastic mirror descent for variationally coherent optimization problems

41. Power control in wireless networks via dual averaging

42. Learning to be green: Robust energy efficiency maximization in dynamic MIMO-OFDM systems

43. Learning in games via reinforcement learning and regularization

44. Energy-efficient power allocation in dynamic multi-carrier systems

45. Adaptive Spectrum Management in MIMO-OFDM Cognitive Radio: An Exponential Learning Approach

46. Cost-efficient power allocation in OFDMA cognitive radio networks

47. Transmit without regrets: Online optimization in MIMO-OFDM cognitive radio systems

48. Entropy-driven dynamics and robust learning procedures in games

49. Higher Order Game Dynamics

50. A new regret analysis for Adam-type algorithms

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