Mertikopoulos, Panayotis

52 publications

TMLR 2025 Characterizing the Convergence of Game Dynamics via Potentialness Martin Bichler, Davide Legacci, Panayotis Mertikopoulos, Matthias Oberlechner, Bary Pradelski

NeurIPS 2025 Efficient Kernelized Learning in Polyhedral Games Beyond Full Information: From Colonel Blotto to Congestion Games Andreas Kontogiannis, Vasilis Pollatos, Gabriele Farina, Panayotis Mertikopoulos, Ioannis Panageas

NeurIPS 2025 Multi-Agent Learning Under Uncertainty: Recurrence vs. Concentration Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose Blanchet

NeurIPS 2025 Robust Equilibria in Continuous Games: From Strategic to Dynamic Robustness Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose Blanchet

AISTATS 2025 Tamed Langevin Sampling Under Weaker Conditions Iosif Lytras, Panayotis Mertikopoulos

ICML 2025 The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations Waı̈ss Azizian, Franck Iutzeler, Jerome Malick, Panayotis Mertikopoulos

ICML 2025 The Impact of Uncertainty on Regularized Learning in Games Pierre-Louis Cauvin, Davide Legacci, Panayotis Mertikopoulos

ICML 2024 A Geometric Decomposition of Finite Games: Convergence vs. Recurrence Under Exponential Weights Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski

NeurIPS 2024 Accelerated Regularized Learning in Finite N-Person Games Kyriakos Lotidis, Angeliki Giannou, Panayotis Mertikopoulos, Nicholas Bambos

NeurIPS 2024 No-Regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests Davide Legacci, Panayotis Mertikopoulos, Christos Papadimitriou, Georgios Piliouras, Bary Pradelski

ICML 2024 The Computational Complexity of Finding Second-Order Stationary Points Andreas Kontogiannis, Vasilis Pollatos, Sotiris Kanellopoulos, Panayotis Mertikopoulos, Aris Pagourtzis, Ioannis Panageas

ICML 2024 What Is the Long-Run Distribution of Stochastic Gradient Descent? a Large Deviations Analysis Waı̈ss Azizian, Franck Iutzeler, Jerome Malick, Panayotis Mertikopoulos

NeurIPS 2023 Exploiting Hidden Structures in Non-Convex Games for Convergence to Nash Equilibrium Iosif Sakos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos, Georgios Piliouras

NeurIPS 2023 Payoff-Based Learning with Matrix Multiplicative Weights in Quantum Games Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos, Jose Blanchet

NeurIPS 2023 Riemannian Stochastic Optimization Methods Avoid Strict Saddle Points Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos

NeurIPS 2023 The Equivalence of Dynamic and Strategic Stability Under Regularized Learning in Games Victor Boone, Panayotis Mertikopoulos

ICML 2022 AdaGrad Avoids Saddle Points Kimon Antonakopoulos, Panayotis Mertikopoulos, Georgios Piliouras, Xiao Wang

ALT 2022 Asymptotic Degradation of Linear Regression Estimates with Strategic Data Sources Benjamin Roussillon, Nicolas Gast, Patrick Loiseau, Panayotis Mertikopoulos

JMLR 2022 Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

ICML 2022 Nested Bandits Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier, Houssam Zenati

NeurIPS 2022 No-Regret Learning in Games with Noisy Feedback: Faster Rates and Adaptivity via Learning Rate Separation Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos

NeurIPS 2022 On the Convergence of Policy Gradient Methods to Nash Equilibria in General Stochastic Games Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil-Vasileios Vlatakis-Gkaragkounis

COLT 2022 The Dynamics of Riemannian Robbins-Monro Algorithms Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause

ICML 2022 UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Levy, Panayotis Mertikopoulos

ICLR 2021 Adaptive Extra-Gradient Methods for Min-Max Optimization and Games Kimon Antonakopoulos, Veronica Belmega, Panayotis Mertikopoulos

NeurIPS 2021 Adaptive First-Order Methods Revisited: Convex Minimization Without Lipschitz Requirements Kimon Antonakopoulos, Panayotis Mertikopoulos

COLT 2021 Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium Yu-Guan Hsieh, Kimon Antonakopoulos, Panayotis Mertikopoulos

NeurIPS 2021 Fast Routing Under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights Dong Quan Vu, Kimon Antonakopoulos, Panayotis Mertikopoulos

NeurIPS 2021 On the Rate of Convergence of Regularized Learning in Games: From Bandits and Uncertainty to Optimism and Beyond Angeliki Giannou, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos

ICML 2021 Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher

NeurIPS 2021 Sifting Through the Noise: Universal First-Order Methods for Stochastic Variational Inequalities Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher

COLT 2021 Survival of the Strictest: Stable and Unstable Equilibria Under Regularized Learning with Partial Information Angeliki Giannou, Emmanouil Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos

COLT 2021 The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

ICML 2021 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher

ICML 2021 Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging Amélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier

ICML 2020 A New Regret Analysis for Adam-Type Algorithms Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher

NeurIPS 2020 Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

ICML 2020 Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael Jordan

NeurIPS 2020 No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Thanasis Lianeas, Panayotis Mertikopoulos, Georgios Piliouras

NeurIPS 2020 On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher

NeurIPS 2020 Online Non-Convex Optimization with Imperfect Feedback Amélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier

ICLR 2020 Online and Stochastic Optimization Beyond Lipschitz Continuity: A Riemannian Approach Kimon Antonakopoulos, E. Veronica Belmega, Panayotis Mertikopoulos

NeurIPS 2019 An Adaptive Mirror-Prox Method for Variational Inequalities with Singular Operators Kimon Antonakopoulos, Veronica Belmega, Panayotis Mertikopoulos

ICML 2019 Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints Nikolaos Liakopoulos, Apostolos Destounis, Georgios Paschos, Thrasyvoulos Spyropoulos, Panayotis Mertikopoulos

NeurIPS 2019 On the Convergence of Single-Call Stochastic Extra-Gradient Methods Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

ICLR 2019 Optimistic Mirror Descent in Saddle-Point Problems: Going the Extra (gradient) Mile Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

NeurIPS 2018 Bandit Learning in Concave N-Person Games Mario Bravo, David Leslie, Panayotis Mertikopoulos

ICML 2018 Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei

NeurIPS 2018 Learning in Games with Lossy Feedback Zhengyuan Zhou, Panayotis Mertikopoulos, Susan Athey, Nicholas Bambos, Peter W. Glynn, Yinyu Ye

NeurIPS 2017 Countering Feedback Delays in Multi-Agent Learning Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Claire Tomlin

NeurIPS 2017 Learning with Bandit Feedback in Potential Games Amélie Heliou, Johanne Cohen, Panayotis Mertikopoulos

NeurIPS 2017 Stochastic Mirror Descent in Variationally Coherent Optimization Problems Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen Boyd, Peter W. Glynn