Mathieu Laurière

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 81

Top Topics

Convergence Analysis

Dynamic Routing

Learning Algorithm

Reinforcement Learning

Top Venues

Publications

Muhammad Aneeq uz Zaman, Alec Koppel, Mathieu Laurière, Tamer Basar
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective. CoRR (2024)
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière, Mengrui Zhang
Analysis of Multiscale Reinforcement Q-Learning Algorithms for Mean Field Control Games. CoRR (2024)
Haoyang Cao, Xin Guo, Mathieu Laurière
Connecting GANs, Mean-Field Games, and Optimal Transport. SIAM J. Appl. Math. 84 (4) (2024)
Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl
Learning Discrete-Time Major-Minor Mean Field Games. AAAI (2024)
Zhouzhou Gu, Mathieu Laurière, Sebastian Merkel, Jonathan Payne
Global Solutions to Master Equations for Continuous Time Heterogeneous Agent Macroeconomic Models. CoRR (2024)
Gökçe Dayanikli, Mathieu Laurière, Jiacheng Zhang
Deep Learning for Population-Dependent Controls in Mean Field Control Problems with Common Noise. AAMAS (2024)
Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective. L4DC (2024)
Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. AAMAS (2024)
Mathieu Laurière, Ludovic Tangpi, Xuchen Zhou
A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents. CoRR (2024)
Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. CoRR (2024)
Muhammad Aneeq uz Zaman, Mathieu Laurière, Alec Koppel, Tamer Basar
Robust Cooperative Multi-Agent Reinforcement Learning:A Mean-Field Type Game Perspective. CoRR (2024)
Diogo Gomes, Julian Gutierrez, Mathieu Laurière
Machine Learning Architectures for Price Formation Models with Common Noise. CDC (2023)
Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl
Learning Discrete-Time Major-Minor Mean Field Games. CoRR (2023)
Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist
On Imitation in Mean-field Games. CoRR (2023)
Lila Fontes, Sophie Laplante, Mathieu Laurière, Alexandre Nolin
The Communication Complexity of Functions with Large Outputs. SIROCCO (2023)
René A. Carmona, Gökçe Dayanikli, François Delarue, Mathieu Laurière
From Nash Equilibrium to Social Optimum and vice versa: a Mean Field Perspective. CoRR (2023)
Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist
On Imitation in Mean-field Games. NeurIPS (2023)
Lila Fontes, Sophie Laplante, Mathieu Laurière, Alexandre Nolin
The communication complexity of functions with large outputs. CoRR (2023)
Lila Fontes, Sophie Laplante, Mathieu Laurière, Alexandre Nolin
The communication complexity of functions with large outputs. Electron. Colloquium Comput. Complex. (2023)
Ruimeng Hu, Mathieu Laurière
Recent Developments in Machine Learning Methods for Stochastic Control and Games. CoRR (2023)
Sebastian Baudelet, Brieuc Frénais, Mathieu Laurière, Amal Machtalay, Yuchen Zhu
Deep Learning for Mean Field Optimal Transport. CoRR (2023)
Alexander Aurell, René Carmona, Gökçe Dayanikli, Mathieu Laurière
Finite State Graphon Games with Applications to Epidemics. Dyn. Games Appl. 12 (1) (2022)
Maximilien Germain, Mathieu Laurière, Huyên Pham, Xavier Warin
DeepSets and Their Derivative Networks for Solving Symmetric PDEs. J. Sci. Comput. 91 (2) (2022)
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Élie, Olivier Pietquin, Matthieu Geist
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. CoRR (2022)
Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS (2022)
René Carmona, Daniel B. Cooney, Christy V. Graves, Mathieu Laurière
Stochastic Graphon Games: I. The Static Case. Math. Oper. Res. 47 (1) (2022)
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. ICML (2022)
Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
Scaling Mean Field Games by Online Mirror Descent. AAMAS (2022)
Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. AAMAS (2022)
Mathieu Laurière, Sarah Perrin, Matthieu Geist, Olivier Pietquin
Learning Mean Field Games: A Survey. CoRR (2022)
Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Eric Goubault, Romuald Elie
Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. AAMAS (2022)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
Generalization in Mean Field Games by Learning Master Policies. AAAI (2022)
Mathieu Laurière, Ludovic Tangpi
Convergence of Large Population Games to Mean Field Games with Interaction Through the Controls. SIAM J. Math. Anal. 54 (3) (2022)
René Carmona, Gökçe Dayanikli, Mathieu Laurière
Mean Field Models to Regulate Carbon Emissions in Electricity Production. Dyn. Games Appl. 12 (3) (2022)
Paul Muller, Romuald Elie, Mark Rowland, Mathieu Laurière, Julien Pérolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls
Learning Correlated Equilibria in Mean-Field Games. CoRR (2022)
Alexander Aurell, René Carmona, Gökçe Dayanikli, Mathieu Laurière
Optimal Incentives to Mitigate Epidemics: A Stackelberg Mean Field Game Approach. SIAM J. Control. Optim. 60 (2) (2022)
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
Unified reinforcement Q-learning for mean field game and control problems. Math. Control. Signals Syst. 34 (2) (2022)
Jimin Lin, Andrea Angiuli, Nils Detering, Jean-Pierre Fouque, Mathieu Laurière
Reinforcement Learning for Intra-and-Inter-Bank Borrowing and Lending Mean Field Control Game. ICAIF (2022)
Mathieu Laurière, Jiahao Song, Qing Tang
Policy iteration method for time-dependent Mean Field Games systems with non-separable Hamiltonians. CoRR (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
Generalization in Mean Field Games by Learning Master Policies. CoRR (2021)
Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. CoRR (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
Mean Field Games Flock! The Reinforcement Learning Way. CoRR (2021)
Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
Scaling up Mean Field Games with Online Mirror Descent. CoRR (2021)
René Carmona, Mathieu Laurière
Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance. CoRR (2021)
René Carmona, Mathieu Laurière
Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games I: The Ergodic Case. SIAM J. Numer. Anal. 59 (3) (2021)
Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Éric Goubault, Romuald Elie
Solving N-player dynamic routing games with congestion: a mean field approach. CoRR (2021)
Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Concave Utility Reinforcement Learning: the Mean-field Game viewpoint. CoRR (2021)
Mathieu Laurière, Gilles Pagès, Olivier Pironneau
Performance of a Markovian neural network versus dynamic programming on a fishing control problem. CoRR (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
Mean Field Games Flock! The Reinforcement Learning Way. IJCAI (2021)
Mathieu Laurière
Numerical Methods for Mean Field Games and Mean Field Type Control. CoRR (2021)
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
Reinforcement Learning for Mean Field Games, with Applications to Economics. CoRR (2021)
Haoyang Cao, Xin Guo, Mathieu Laurière
Connecting GANs and MFGs. CoRR (2020)
Titouan Carette, Mathieu Laurière, Frédéric Magniez
Extended Learning Graphs for Triangle Finding. Algorithmica 82 (4) (2020)
Arthur Charpentier, Romuald Elie, Mathieu Laurière, Viet Chi Tran
COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability. CoRR (2020)
Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
Unified Reinforcement Q-Learning for Mean Field Game and Control Problems. CoRR (2020)
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. CoRR (2020)
René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games. CoRR (2020)
Laura Leal, Mathieu Laurière, Charles-Albert Lehalle
Learning a functional control for high-frequency finance. CoRR (2020)
René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games. CDC (2020)
Yves Achdou, Mathieu Laurière
Mean Field Games and Applications: Numerical Aspects. CoRR (2020)
René Carmona, Kenza Hamidouche, Mathieu Laurière, Zongjun Tan
Linear-Quadratic Zero-Sum Mean-Field Type Games: Optimality Conditions and Policy Optimization. CoRR (2020)
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. NeurIPS (2020)
Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
On the Convergence of Model Free Learning in Mean Field Games. AAAI (2020)
René Carmona, Mathieu Laurière
Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II - The Finite Horizon Case. CoRR (2019)
René Carmona, Mathieu Laurière, Zongjun Tan
Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning. CoRR (2019)
René Carmona, Mathieu Laurière
Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: I - The Ergodic Case. CoRR (2019)
Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
Approximate Fictitious Play for Mean Field Games. CoRR (2019)
René Carmona, Mathieu Laurière, Zongjun Tan
Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods. CoRR (2019)
Mathieu Laurière, Laurent Mertz
Penalization of Nonsmooth Dynamical Systems with Noise: Ergodicity and Asymptotic Formulae for Threshold Crossings Probabilities. SIAM J. Appl. Dyn. Syst. 18 (2) (2019)
Cyril Feau, Mathieu Laurière, Laurent Mertz
Asymptotic formulae for the risk of failure related to an elasto-plastic problem with noise. Asymptot. Anal. 106 (1) (2018)
Mathieu Laurière, Dave Touchette
The Flow of Information in Interactive Quantum Protocols: the Cost of Forgetting. ITCS (2017)
Titouan Carette, Mathieu Laurière, Frédéric Magniez
Extended Learning Graphs for Triangle Finding. STACS (2017)
Mathieu Laurière, Dave Touchette
The Flow of Information in Interactive Quantum Protocols: the Cost of Forgetting. CoRR (2017)
Iordanis Kerenidis, Mathieu Laurière, Francois Le Gall, Mathys Rennela
Information cost of quantum communication protocols. Quantum Inf. Comput. 16 (3&4) (2016)
Sophie Laplante, Mathieu Laurière, Alexandre Nolin, Jérémie Roland, Gabriel Senno
Robust Bell Inequalities from Communication Complexity. TQC (2016)
Titouan Carette, Mathieu Laurière, Frédéric Magniez
Extended Learning Graphs for Triangle Finding. CoRR (2016)
Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland
Relative Discrepancy Does Not Separate Information and Communication Complexity. ACM Trans. Comput. Theory 9 (1) (2016)
Yves Achdou, Mathieu Laurière
Mean Field Type Control with Congestion (II): An Augmented Lagrangian Method. CoRR (2016)
Mathieu Laurière, Olivier Pironneau
Dynamic Programming for Mean-Field Type Control. J. Optim. Theory Appl. 169 (3) (2016)
Charles Bascou, Valentin Emiya, Mathieu Laurière
The problem of musical gesture continuation and a baseline system. ICMC (2016)
Sophie Laplante, Mathieu Laurière, Alexandre Nolin, Jérémie Roland, Gabriel Senno
Robust Bell inequalities from communication complexity. CoRR (2016)
Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland
Relative Discrepancy Does not Separate Information and Communication Complexity. ICALP (1) (2015)
Lila Fontes, Rahul Jain, Iordanis Kerenidis, Sophie Laplante, Mathieu Laurière, Jérémie Roland
Relative Discrepancy does not separate Information and Communication Complexity. Electron. Colloquium Comput. Complex. 22 (2015)
Iordanis Kerenidis, Mathieu Laurière, François Le Gall, Mathys Rennela
Privacy in Quantum Communication Complexity. CoRR (2014)
Iordanis Kerenidis, Mathieu Laurière, David Xiao
New Lower Bounds for Privacy in Communication Protocols. ICITS (2013)
Iordanis Kerenidis, Mathieu Laurière, David Xiao
New lower bounds for privacy in communication protocols. Electron. Colloquium Comput. Complex. 20 (2013)