Asymptotically Optimal Communication in Simple Mechanisms. - Ioannis Anagnostides; Dimitris Fotakis 001; Panagiotis Patsilinakos (SAGT, 2020)

Solving Zero-Sum Games through Alternating Projections. - Ioannis Anagnostides; Paolo Penna (CoRR, 2020)

A Robust Framework for Analyzing Gradient-Based Dynamics in Bilinear Games. - Ioannis Anagnostides; Paolo Penna (CoRR, 2020)

Robust Learning under Strong Noise via SQs. - Ioannis Anagnostides; Themis Gouleakis; Ali Marashian (AISTATS, 2021)

Deterministic Distributed Algorithms and Lower Bounds in the Hybrid Model. - Ioannis Anagnostides; Themis Gouleakis (DISC, 2021)

Dimensionality, Coordination, and Robustness in Voting. - Ioannis Anagnostides; Dimitris Fotakis 001; Panagiotis Patsilinakos (CoRR, 2021)

Accelerated Distributed Laplacian Solvers via Shortcuts. - Ioannis Anagnostides; Themis Gouleakis; Christoph Lenzen 001 (CoRR, 2021)

Dimensionality and Coordination in Voting: The Distortion of STV. - Ioannis Anagnostides; Dimitris Fotakis 001; Panagiotis Patsilinakos (AAAI, 2022)

On Last-Iterate Convergence Beyond Zero-Sum Games. - Ioannis Anagnostides; Ioannis Panageas; Gabriele Farina; Tuomas Sandholm (ICML, 2022)

Uncoupled Learning Dynamics with O(log T) Swap Regret in Multiplayer Games. - Ioannis Anagnostides; Gabriele Farina; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Tuomas Sandholm (NeurIPS, 2022)

Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games. - Ioannis Anagnostides; Gabriele Farina; Ioannis Panageas; Tuomas Sandholm (NeurIPS, 2022)

Near-Optimal No-Regret Learning Dynamics for General Convex Games. - Gabriele Farina; Ioannis Anagnostides; Haipeng Luo; Chung-Wei Lee; Christian Kroer; Tuomas Sandholm (NeurIPS, 2022)

Brief Announcement: Almost Universally Optimal Distributed Laplacian Solver. - Ioannis Anagnostides; Christoph Lenzen 001; Bernhard Haeupler; Goran Zuzic; Themis Gouleakis (PODC, 2022)

Faster No-Regret Learning Dynamics for Extensive-Form Correlated and Coarse Correlated Equilibria. - Ioannis Anagnostides; Gabriele Farina; Christian Kroer; Andrea Celli; Tuomas Sandholm (EC, 2022)

Frequency-Domain Representation of First-Order Methods: A Simple and Robust Framework of Analysis. - Ioannis Anagnostides; Ioannis Panageas (SOSA, 2022)

Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games. - Ioannis Anagnostides; Constantinos Daskalakis; Gabriele Farina; Maxwell Fishelson; Noah Golowich; Tuomas Sandholm (STOC, 2022)

Uncoupled Learning Dynamics with O(log T) Swap Regret in Multiplayer Games. - Ioannis Anagnostides; Gabriele Farina; Christian Kroer; Chung-Wei Lee; Haipeng Luo; Tuomas Sandholm (CoRR, 2022)

Near-Optimal No-Regret Learning for General Convex Games. - Gabriele Farina; Ioannis Anagnostides; Haipeng Luo; Chung-Wei Lee; Christian Kroer; Tuomas Sandholm (CoRR, 2022)

Sampling and Optimal Preference Elicitation in Simple Mechanisms. - Ioannis Anagnostides; Dimitris Fotakis 001; Panagiotis Patsilinakos (CoRR, 2022)

Metric-Distortion Bounds under Limited Information. - Ioannis Anagnostides; Dimitris Fotakis 001; Panagiotis Patsilinakos (J. Artif. Intell. Res., 2022)

Meta-Learning in Games. - Keegan Harris; Ioannis Anagnostides; Gabriele Farina; Mikhail Khodak; Steven Wu 001; Tuomas Sandholm (ICLR, 2023)

Efficiently Computing Nash Equilibria in Adversarial Team Markov Games. - Fivos Kalogiannis; Ioannis Anagnostides; Ioannis Panageas; Emmanouil V. Vlatakis-Gkaragkounis; Vaggos Chatziafratis; Stelios Andrew Stavroulakis (ICLR, 2023)

Near-Optimal Φ-Regret Learning in Extensive-Form Games. - Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm (ICML, 2023)

On the Convergence of No-Regret Learning Dynamics in Time-Varying Games. - Ioannis Anagnostides; Ioannis Panageas; Gabriele Farina; Tuomas Sandholm (NeurIPS, 2023)

On the Interplay between Social Welfare and Tractability of Equilibria. - Ioannis Anagnostides; Tuomas Sandholm (NeurIPS, 2023)

Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games. - Brian Hu Zhang; Gabriele Farina; Ioannis Anagnostides; Federico Cacciamani; Stephen McAleer; Andreas A. Haupt; Andrea Celli; Nicola Gatti 001; Vincent Conitzer; Tuomas Sandholm (NeurIPS, 2023)

Algorithms and Complexity for Computing Nash Equilibria in Adversarial Team Games. - Ioannis Anagnostides; Fivos Kalogiannis; Ioannis Panageas; Emmanouil-Vasileios Vlatakis-Gkaragkounis; Stephen McAleer (EC, 2023)

Steering No-Regret Learners to Optimal Equilibria. - Brian Hu Zhang; Gabriele Farina; Ioannis Anagnostides; Federico Cacciamani; Stephen Marcus McAleer; Andreas Alexander Haupt; Andrea Celli; Nicola Gatti 001; Vincent Conitzer; Tuomas Sandholm (CoRR, 2023)

Almost universally optimal distributed Laplacian solvers via low-congestion shortcuts. - Ioannis Anagnostides; Christoph Lenzen 001; Bernhard Haeupler; Goran Zuzic; Themis Gouleakis (Distributed Comput., 2023)

Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property. - Ioannis Anagnostides; Ioannis Panageas; Gabriele Farina; Tuomas Sandholm (AAAI, 2024)

On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games. - Ioannis Anagnostides; Alkis Kalavasis; Tuomas Sandholm; Manolis Zampetakis (ITCS, 2024)

Convergence of $ text{log}(1/ epsilon)$ for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis. - Ioannis Anagnostides; Tuomas Sandholm (NeurIPS, 2024)

Efficient $ Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games. - Brian Hu Zhang; Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm (NeurIPS, 2024)

Steering No-Regret Learners to a Desired Equilibrium. - Brian Hu Zhang; Gabriele Farina; Ioannis Anagnostides; Federico Cacciamani; Stephen McAleer; Andreas A. Haupt; Andrea Celli; Nicola Gatti 001; Vincent Conitzer; Tuomas Sandholm (EC, 2024)

Efficient Φ-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games. - Brian Hu Zhang; Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm (CoRR, 2024)

Convergence of log(1/ε) for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis. - Ioannis Anagnostides; Tuomas Sandholm (CoRR, 2024)

Barriers to Welfare Maximization with No-Regret Learning. - Ioannis Anagnostides; Alkis Kalavasis; Tuomas Sandholm (CoRR, 2024)

Computational Lower Bounds for Regret Minimization in Normal-Form Games. - Ioannis Anagnostides; Alkis Kalavasis; Tuomas Sandholm (CoRR, 2024)

The Value of Recall in Extensive-Form Games. - Ratip Emin Berker; Emanuel Tewolde; Ioannis Anagnostides; Tuomas Sandholm; Vincent Conitzer (AAAI, 2025)

Learning and Computation of Φ-Equilibria at the Frontier of Tractability. - Brian Hu Zhang; Ioannis Anagnostides; Emanuel Tewolde; Ratip Emin Berker; Gabriele Farina; Vincent Conitzer; Tuomas Sandholm (EC, 2025)

Computational Lower Bounds for No-Regret Learning in Normal-Form Games. - Ioannis Anagnostides; Alkis Kalavasis; Tuomas Sandholm (STOC, 2025)

The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games. - Ioannis Anagnostides; Ioannis Panageas; Tuomas Sandholm; Jingming Yan (CoRR, 2025)

Expected Variational Inequalities. - Brian Hu Zhang; Ioannis Anagnostides; Emanuel Tewolde; Ratip Emin Berker; Gabriele Farina; Vincent Conitzer; Tuomas Sandholm (CoRR, 2025)

A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition. - Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm; Brian Hu Zhang (CoRR, 2025)