| Market Making with Scaled Beta Policies. | 0 | 0.34 | 2022 |
| Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. | 0 | 0.34 | 2022 |
| Generative Models over Neural Controllers for Transfer Learning. | 0 | 0.34 | 2022 |
| Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures. | 0 | 0.34 | 2022 |
| A Faster Algorithm For Finding Tarski Fixed Points | 0 | 0.34 | 2021 |
| Trading via selective classification. | 0 | 0.34 | 2021 |
| The Complexity of Gradient Descent (Invited Talk). | 0 | 0.34 | 2021 |
| Difference Rewards Policy Gradients | 0 | 0.34 | 2021 |
| Robust Market Making via Adversarial Reinforcement Learning | 0 | 0.34 | 2020 |
| One-Clock Priced Timed Games are PSPACE-hard | 0 | 0.34 | 2020 |
| Mapping the geodemographics of digital inequality in Great Britain: An integration of machine learning into small area estimation | 1 | 0.35 | 2020 |
| Tree Polymatrix Games are PPAD-hard | 0 | 0.34 | 2020 |
| Evolving Indoor Navigational Strategies Using Gated Recurrent Units In NEAT. | 0 | 0.34 | 2019 |
| Preface to the Special Issue on Algorithmic Game Theory. | 0 | 0.34 | 2019 |
| Computing Stable Outcomes in Symmetric Additively Separable Hedonic Games. | 0 | 0.34 | 2019 |
| The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning. | 0 | 0.34 | 2019 |
| Unique End of Potential Line. | 0 | 0.34 | 2018 |
| Market Making Via Reinforcement Learning | 0 | 0.34 | 2018 |
| Space Debris Removal: Learning to Cooperate and the Price of Anarchy. | 1 | 0.40 | 2018 |
| Beyond Local Nash Equilibria for Adversarial Networks. | 3 | 0.38 | 2018 |
| End of Potential Line. | 2 | 0.37 | 2018 |
| Negative Update Intervals in Deep Multi-Agent Reinforcement Learning | 0 | 0.34 | 2018 |
| Reachability Switching Games | 0 | 0.34 | 2018 |
| Inapproximability results for constrained approximate Nash equilibria. | 1 | 0.36 | 2018 |
| Lenient Multi-Agent Deep Reinforcement Learning | 6 | 0.42 | 2018 |
| GANGs: Generative Adversarial Network Games. | 2 | 0.49 | 2017 |
| Computing Constrained Approximate Equilibria in Polymatrix Games. | 1 | 0.36 | 2017 |
| Symmetric Decomposition Of Asymmetric Games | 1 | 0.48 | 2017 |
| CLS: New Problems and Completeness. | 0 | 0.34 | 2017 |
| Inapproximability Results for Approximate Nash Equilibria. | 5 | 0.41 | 2016 |
| Space Debris Removal: A Game Theoretic Analysis. | 1 | 0.39 | 2016 |
| The Complexity of All-switches Strategy Improvement. | 0 | 0.34 | 2016 |
| An Empirical Study on Computing Equilibria in Polymatrix Games. | 2 | 0.37 | 2016 |
| Distributed Methods for Computing Approximate Equilibria | 6 | 0.45 | 2015 |
| Computing stable outcomes in symmetric additively-separable hedonic games. | 0 | 0.34 | 2015 |
| Unit Vector Games | 0 | 0.34 | 2015 |
| An Empirical Study of Finding Approximate Equilibria in Bimatrix Games. | 4 | 0.46 | 2015 |
| Cooperative max games and agent failures | 9 | 0.49 | 2014 |
| Computing Approximate Nash Equilibria in Polymatrix Games. | 2 | 0.38 | 2014 |
| The Complexity of the Simplex Method. | 5 | 0.47 | 2014 |
| Game Theory Explorer - Software for the Applied Game Theorist. | 4 | 0.44 | 2014 |
| A data rich money market model - agent-based modelling for financial stability | 0 | 0.34 | 2014 |
| Equilibrium Computation (Dagstuhl Seminar 14342). | 0 | 0.34 | 2014 |
| Learning equilibria of games via payoff queries | 11 | 0.61 | 2013 |
| Polylogarithmic Supports are required for Approximate Well-Supported Nash Equilibria below 2/3. | 7 | 0.60 | 2013 |
| Finding approximate nash equilibria of bimatrix games via payoff queries | 6 | 0.50 | 2013 |
| Approximate well-supported nash equilibria below two-thirds | 15 | 0.88 | 2012 |
| High-Frequency Trading: The Faster, the Better? | 2 | 0.42 | 2012 |
| Computing stable outcomes in hedonic games with voting-based deviations | 12 | 0.74 | 2011 |
| On the approximation performance of fictitious play in finite games | 0 | 0.34 | 2011 |
