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Ioannis Panageas

32 papers · 2017–2024 · 8 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ 🏃 Academic Marathon (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) 🐝 Cross-Pollinator (9)
🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) 🏃 Academic Marathon (7) 👑 Triple Crown 🏆 Grand Slam 🔬 Deep Specialist (10) 🏆 Keyword Champion (2) 💎 Century Club (32) Prolific Year (8) 🔥 Unstoppable (8) 🗃️ Keyword Collector (101)

Conferences

NIPS (11) ICLR (6) ICML (5) AISTATS (4) AAAI (3) ALT (1) IJCAI (1) UAI (1)

Papers

Learning Nash Equilibria in Rank-1 Games ICLR 2024 Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games UAI 2024 Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem NIPS 2024 Beating Price of Anarchy and Gradient Descent without Regret in Potential Games ICLR 2024 Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property AAAI 2024 Computing Nash Equilibria in Potential Games with Private Uncoupled Constraints AAAI 2024 The Computational Complexity of Finding Second-Order Stationary Points ICML 2024 Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. ICML 2023 Towards convergence to Nash equilibria in two-team zero-sum games ICLR 2023 Efficiently Computing Nash Equilibria in Adversarial Team Markov Games ICLR 2023 On the Convergence of No-Regret Learning Dynamics in Time-Varying Games NIPS 2023 On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails NIPS 2023 Exponential Lower Bounds for Fictitious Play in Potential Games NIPS 2023 Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria NIPS 2023 Mean Estimation of Truncated Mixtures of Two Gaussians: A Gradient Based Approach AAAI 2023 On Scrambling Phenomena for Randomly Initialized Recurrent Networks NIPS 2022 On Last-Iterate Convergence Beyond Zero-Sum Games ICML 2022 Independent Natural Policy Gradient always converges in Markov Potential Games AISTATS 2022 Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games NIPS 2022 Accelerated Multiplicative Weights Update Avoids Saddle Points Almost Always IJCAI 2022 Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games ICLR 2022 Efficient Statistics for Sparse Graphical Models from Truncated Samples AISTATS 2021 Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes AISTATS 2021 Better depth-width trade-offs for neural networks through the lens of dynamical systems ICML 2020 On the Analysis of EM for truncated mixtures of two Gaussians ALT 2020 Logistic regression with peer-group effects via inference in higher-order Ising models AISTATS 2020 Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev NIPS 2020 Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem ICLR 2020 Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always ICML 2019 First-order methods almost always avoid saddle points: The case of vanishing step-sizes NIPS 2019 The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization NIPS 2018 Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos NIPS 2017