Matthieu Geist
58 papers · 2012–2025 · 13 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 (73) π Conference Polyglot Β· Gold π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Dynamic Duo
(35)
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Deep Specialist
(28)
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Prolific Year Β· Prolific
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Unstoppable Β· Bronze
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The Questioner
(3)
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Century Club Β· Silver
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Renaissance Researcher
(5)
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Keyword Collector
(217)
Venues
Top co-authors
Research topics
Machine Learning
(48)
Reinforcement Learning
(46)
Methods
(43)
Learning Types Β· Machine Learning
(31)
Optimization & Theory
(29)
Artificial Intelligence
(23)
Core AI
(22)
Deep Learning
(18)
Learning Types Β· Deep Learning
(14)
Mathematics & Optimization
(8)
Optimization
(8)
Applications
(6)
Core Methods
(6)
Architectures
(4)
Application Areas
(3)
Keywords
reinforcement learning
(20)
markov decision process
(8)
mean field game
(8)
imitation learning
(8)
deep reinforcement learning
(7)
continuous control
(7)
multi-agent system
(7)
reward function
(6)
nash equilibrium
(6)
fictitious play
(6)
value iteration
(6)
sample complexity
(6)
policy optimization
(5)
policy learning
(5)
policy iteration
(5)
offline reinforcement learning
(4)
off-policy learning
(4)
neural network
(4)
inverse reinforcement learning
(3)
robust optimization
(3)
Papers
Self-Improving Robust Preference Optimization
ICLR 2025
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
ICLR 2024
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion
EMNLP 2024
Imitating Language via Scalable Inverse Reinforcement Learning
NeurIPS 2024
Learning Discrete-Time Major-Minor Mean Field Games
AAAI 2024
MusicRL: Aligning Music Generation to Human Preferences
ICML 2024
Nash Learning from Human Feedback
ICML 2024
Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms
NeurIPS 2024
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
ICLR 2024
Periodic agent-state based Q-learning for POMDPs
NeurIPS 2024
Time-Constrained Robust MDPs
NeurIPS 2024
Towards Minimax Optimality of Model-based Robust Reinforcement Learning
UAI 2024
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
ICML 2023
Extreme Q-Learning: MaxEnt RL without Entropy
ICLR 2023
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
ACL 2023
On Imitation in Mean-field Games
NeurIPS 2023
Policy Gradient for Rectangular Robust Markov Decision Processes
NeurIPS 2023
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
ICML 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
ICML 2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
NeurIPS 2023
A general class of surrogate functions for stable and efficient reinforcement learning
AISTATS 2022
Continuous Control with Action Quantization from Demonstrations
ICML 2022
Generalization in Mean Field Games by Learning Master Policies
AAAI 2022
Implicitly Regularized RL with Implicit Q-values
AISTATS 2022
Large Batch Experience Replay
ICML 2022
Learning Energy Networks with Generalized Fenchel-Young Losses
NeurIPS 2022
Offline Reinforcement Learning as Anti-exploration
AAAI 2022
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
ICML 2022
Adversarially Guided Actor-Critic
ICLR 2021
Hyperparameter Selection for Imitation Learning
ICML 2021
Learning Behaviors through Physics-driven Latent Imagination
CoRL 2021
Mean Field Games Flock! The Reinforcement Learning Way
IJCAI 2021
Offline Reinforcement Learning with Pseudometric Learning
ICML 2021
Primal Wasserstein Imitation Learning
ICLR 2021
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
NeurIPS 2021
Twice regularized MDPs and the equivalence between robustness and regularization
NeurIPS 2021
What Matters for Adversarial Imitation Learning?
NeurIPS 2021
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
ICLR 2021
Deep Conservative Policy Iteration
AAAI 2020
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
NeurIPS 2020
Foolproof Cooperative Learning
ACML 2020
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
NeurIPS 2020
Momentum in Reinforcement Learning
AISTATS 2020
Munchausen Reinforcement Learning
NeurIPS 2020
On the Convergence of Model Free Learning in Mean Field Games
AAAI 2020
Self-Attentional Credit Assignment for Transfer in Reinforcement Learning
IJCAI 2020
A Theory of Regularized Markov Decision Processes
ICML 2019
ELF: Embedded Localisation of Features in Pre-Trained CNN
ICCV 2019
Learning from a Learner
ICML 2019
Is the Bellman residual a bad proxy?
NeurIPS 2017
Reconstruct & Crush Network
NeurIPS 2017
Softened Approximate Policy Iteration for Markov Games
ICML 2016
Approximate Modified Policy Iteration and its Application to the Game of Tetris
JMLR 2015
Inverse Reinforcement Learning in Relational Domains
IJCAI 2015
Difference of Convex Functions Programming for Reinforcement Learning
NeurIPS 2014
Off-policy Learning With Eligibility Traces: A Survey
JMLR 2014
A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics
JMLR 2013
Inverse Reinforcement Learning through Structured Classification
NeurIPS 2012