Ioannis Panageas
32 papers · 2017–2024 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (36) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(12)
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Grand Slam
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Triple Crown
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Topic Evolution
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Keyword Champion
(3)
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Keyword Pioneer
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Keyword Collector
(122)
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Century Club Β· Bronze
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Prolific Year Β· Productive
Top co-authors
Research topics
Machine Learning
(27)
Optimization & Theory Β· Machine Learning
(23)
Mathematics & Optimization
(20)
Artificial Intelligence
(19)
Core AI
(19)
Optimization
(17)
Learning Types
(9)
Reinforcement Learning
(4)
Core Methods
(4)
Mathematics
(4)
Methods
(4)
Deep Learning
(2)
Architectures
(2)
Bayesian & Probabilistic
(1)
Optimization & Theory Β· Deep Learning
(1)
Keywords
nash equilibrium
(16)
dynamical system
(7)
zero-sum game
(7)
multi-agent system
(5)
multi-agent reinforcement learning
(5)
last-iterate convergence
(5)
markov game
(4)
policy gradient
(4)
min-max optimization
(3)
multiplicative weights update
(3)
gradient descent
(3)
optimistic gradient descent
(3)
potential game
(3)
expectation maximization
(2)
non-convex optimization
(2)
online learning
(2)
optimistic method
(2)
convergence guarantee
(2)
mirror descent
(2)
game theory
(2)
Papers
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
ICLR 2024
Computing Nash Equilibria in Potential Games with Private Uncoupled Constraints
AAAI 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
NeurIPS 2024
Learning Nash Equilibria in Rank-1 Games
ICLR 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property
AAAI 2024
The Computational Complexity of Finding Second-Order Stationary Points
ICML 2024
Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
ICLR 2023
Exponential Lower Bounds for Fictitious Play in Potential Games
NeurIPS 2023
Mean Estimation of Truncated Mixtures of Two Gaussians: A Gradient Based Approach
AAAI 2023
On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
NeurIPS 2023
On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails
NeurIPS 2023
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
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria
NeurIPS 2023
Accelerated Multiplicative Weights Update Avoids Saddle Points Almost Always
IJCAI 2022
Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games
ICLR 2022
Independent Natural Policy Gradient always converges in Markov Potential Games
AISTATS 2022
On Last-Iterate Convergence Beyond Zero-Sum Games
ICML 2022
On Scrambling Phenomena for Randomly Initialized Recurrent Networks
NeurIPS 2022
Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games
NeurIPS 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
Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem
ICLR 2020
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev
NeurIPS 2020
Logistic regression with peer-group effects via inference in higher-order Ising models
AISTATS 2020
On the Analysis of EM for truncated mixtures of two Gaussians
ALT 2020
First-order methods almost always avoid saddle points: The case of vanishing step-sizes
NeurIPS 2019
Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always
ICML 2019
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
NeurIPS 2018
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos
NeurIPS 2017