Olivier Pietquin
58 papers · 2011–2025 · 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 (77) 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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Keyword Trendsetter Combo
(3)
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Deep Specialist
(27)
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Keyword Champion
(2)
π§
Keyword Pioneer
π
Triple Crown
π
Grand Slam
π
Renaissance Researcher
(5)
π₯
Unstoppable Β· Silver
β
The Questioner
(5)
β‘
Prolific Year Β· Prolific
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Conference Pioneer
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Century Club Β· Silver
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Trend Setter
ποΈ
Keyword Collector
(221)
Venues
Top co-authors
Research topics
Machine Learning
(41)
Reinforcement Learning
(41)
Methods
(37)
Learning Types Β· Machine Learning
(33)
Artificial Intelligence
(32)
Core AI
(31)
Optimization & Theory
(19)
Deep Learning
(15)
Learning Types Β· Deep Learning
(12)
Applications
(11)
Mathematics & Optimization
(7)
Optimization
(7)
Natural Language Processing
(5)
Generation
(4)
Core Methods
(3)
Keywords
reinforcement learning
(21)
deep reinforcement learning
(9)
multi-agent system
(8)
mean field game
(7)
fictitious play
(7)
nash equilibrium
(6)
policy learning
(6)
imitation learning
(6)
value iteration
(5)
reward function
(5)
policy iteration
(5)
continuous control
(5)
markov decision process
(4)
policy optimization
(4)
markov game
(4)
game theory
(4)
neural network
(4)
sample complexity
(3)
entropy regularization
(3)
approximate dynamic programming
(3)
Papers
NatureLM-audio: an Audio-Language Foundation Model for Bioacoustics
ICLR 2025
Self-Improving Robust Preference Optimization
ICLR 2025
Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs
ACL 2024
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion
EMNLP 2024
Countering Reward Over-Optimization in LLM with Demonstration-Guided Reinforcement Learning
ACL 2024
Learning Discrete-Time Major-Minor Mean Field Games
AAAI 2024
MusicRL: Aligning Music Generation to Human Preferences
ICML 2024
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
ACL 2023
On Imitation in Mean-field Games
NeurIPS 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
ICML 2023
Continuous Control with Action Quantization from Demonstrations
ICML 2022
Emergent Communication: Generalization and Overfitting in Lewis Games
NeurIPS 2022
Generalization in Mean Field Games by Learning Master Policies
AAAI 2022
Implicitly Regularized RL with Implicit Q-values
AISTATS 2022
Learning Natural Language Generation with Truncated Reinforcement Learning
NAACL 2022
Offline Reinforcement Learning as Anti-exploration
AAAI 2022
On the role of population heterogeneity in emergent communication
ICLR 2022
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
ICML 2022
Adversarially Guided Actor-Critic
ICLR 2021
Donβt Do What Doesnβt Matter: Intrinsic Motivation with Action Usefulness
IJCAI 2021
Hyperparameter Selection for Imitation Learning
ICML 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
What Matters for Adversarial Imitation Learning?
NeurIPS 2021
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
ICLR 2021
A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning
Interspeech 2020
Countering Language Drift with Seeded Iterated Learning
ICML 2020
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
Supervised Seeded Iterated Learning for Interactive Language Learning
EMNLP 2020
A Theory of Regularized Markov Decision Processes
ICML 2019
Budgeted Reinforcement Learning in Continuous State Space
NeurIPS 2019
Learning from a Learner
ICML 2019
Actor-Critic Fictitious Play in Simultaneous Move Multistage Games
AISTATS 2018
Noisy Networks For Exploration
ICLR 2018
End-to-end optimization of goal-driven and visually grounded dialogue systems
IJCAI 2017
GuessWhat?! Visual Object Discovery Through Multi-Modal Dialogue
CVPR 2017
Is the Bellman residual a bad proxy?
NeurIPS 2017
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data
AISTATS 2017
Modulating early visual processing by language
NeurIPS 2017
A Stochastic Model for Computer-Aided Human-Human Dialogue
Interspeech 2016
On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games
AISTATS 2016
PAC learning of Probabilistic Automaton based on the Method of Moments
ICML 2016
Softened Approximate Policy Iteration for Markov Games
ICML 2016
Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games
ICML 2015
Inverse Reinforcement Learning in Relational Domains
IJCAI 2015
Difference of Convex Functions Programming for Reinforcement Learning
NeurIPS 2014
Inverse Reinforcement Learning through Structured Classification
NeurIPS 2012
Statistical User Simulation for Spoken Dialogue Systems: What for, Which Data, Which Future?
NAACL 2012
Training a BN-based user model for dialogue simulation with missing data
IJCNLP 2011