ASR system modeling for automatic evaluation and optimization of dialogue systems. - Olivier Pietquin; Steve Renals (ICASSP, 2002)

Aided design of finite-state dialogue management systems. - Olivier Pietquin; Thierry Dutoit (ICME, 2003)

Une description probabiliste de la communication parlée entre homme et machine. - Olivier Pietquin (IHM, 2004)

A Probabilistic Description of Man-Machine Spoken Communication. - Olivier Pietquin (ICME, 2005)

Comparing ASR modeling methods for spoken dialogue simulation and optimal strategy learning. - Olivier Pietquin; Richard Beaufort (INTERSPEECH, 2005)

Réseau bayesien pour un modèle d'utilisateur et un module de compréhension pour l'optimisation des systèmes de dialogues. - Olivier Pietquin (TALN (Articles courts), 2005)

Machine Learning for Spoken Dialogue Management: An Experiment with Speech-Based Database Querying. - Olivier Pietquin (AIMSA, 2006)

Dynamic Bayesian Networks for NLU Simulation with Applications to Dialog Optimal Strategy Learning. - Olivier Pietquin; Thierry Dutoit (ICASSP (1), 2006)

Consistent Goal-Directed User Model for Realisitc Man-Machine Task-Oriented Spoken Dialogue Simulation. - Olivier Pietquin (ICME, 2006)

A probabilistic framework for dialog simulation and optimal strategy learning. - Olivier Pietquin; Thierry Dutoit (IEEE Trans. Speech Audio Process., 2006)

Learning to Ground in Spoken Dialogue Systems. - Olivier Pietquin (ICASSP (4), 2007)

Machine learning for spoken dialogue systems. - Oliver Lemon; Olivier Pietquin (INTERSPEECH, 2007)

Functional semi-automated segmentation of renal DCE-MRI sequences using a Growing Neural Gas algorithm. - Beatrice Chevaillier; Damien Mandry; Yannick Ponvianne; Jean-Luc Collette; Michel Claudon; Olivier Pietquin (EUSIPCO, 2008)

Bayesian Reward Filtering. - Matthieu Geist; Olivier Pietquin; Gabriel Fricout (EWRL, 2008)

Functional semi-automated segmentation of renal DCE-MRI sequences. - Beatrice Chevaillier; Yannick Ponvianne; Jean-Luc Collette; Damien Mandry; Michel Claudon; Olivier Pietquin (ICASSP, 2008)

Adaptive RR prediction for cardiac MRI. - Julien Oster; Olivier Pietquin; Gilles Bosser (ICASSP, 2008)

Kalman Temporal Differences: The deterministic case. - Matthieu Geist; Olivier Pietquin; Gabriel Fricout (ADPRL, 2009)

Kernelizing Vector Quantization Algorithms. - Matthieu Geist; Olivier Pietquin; Gabriel Fricout (ESANN, 2009)

A specific QRS detector for electrocardiography during MRI: Using wavelets and local regularity characterization. - Julien Oster; Olivier Pietquin; Roger Abächerli; Michel Kraemer; Jacques Felblinger (ICASSP, 2009)

Tracking in Reinforcement Learning. - Matthieu Geist; Olivier Pietquin; Gabriel Fricout (ICONIP (1), 2009)

Online speaker diarization with a size-monitored growing neural gas algorithm. - Jean-Louis Gutzwiller; Hervé Frezza-Buet; Olivier Pietquin (ESANN, 2010)

Objective assessment of renal DCE-MRI image segmentation. - Beatrice Chevaillier; Jean-Luc Collette; Damien Mandry; Michel Claudon; Olivier Pietquin (EUSIPCO, 2010)

Bayesian framework for artifact reduction on ECG IN MRI. - Julien Oster; Olivier Pietquin; Michel Kraemer; Jacques Felblinger (ICASSP, 2010)

Statistically linearized least-squares temporal differences. - Matthieu Geist; Olivier Pietquin (ICUMT, 2010)

Eligibility traces through colored noises. - Matthieu Geist; Olivier Pietquin (ICUMT, 2010)

Optimizing spoken dialogue management with fitted value iteration. - Senthilkumar Chandramohan; Matthieu Geist; Olivier Pietquin (INTERSPEECH, 2010)

Single-speaker/multi-speaker co-channel speech classification. - Stéphane Rossignol; Olivier Pietquin (INTERSPEECH, 2010)

User and Noise Adaptive Dialogue Management Using Hybrid System Actions. - Senthilkumar Chandramohan; Olivier Pietquin (IWSDS, 2010)

Simulation of the Grounding Process in Spoken Dialog Systems with Bayesian Networks. - Stéphane Rossignol; Olivier Pietquin; Michel Ianotto (IWSDS, 2010)

Revisiting Natural Actor-Critics with Value Function Approximation. - Matthieu Geist; Olivier Pietquin (MDAI, 2010)

Sparse Approximate Dynamic Programming for Dialog Management. - Senthilkumar Chandramohan; Matthieu Geist; Olivier Pietquin (SIGDIAL Conference, 2010)

Kalman Temporal Differences. - Matthieu Geist; Olivier Pietquin (J. Artif. Intell. Res., 2010)

Différences temporelles de Kalman. Cas déterministe. - Matthieu Geist; Olivier Pietquin; Gabriel Fricout (Rev. d'Intelligence Artif., 2010)

Nonlinear Bayesian Filtering for Denoising of Electrocardiograms Acquired in a Magnetic Resonance Environment. - Julien Oster; Olivier Pietquin; Michel Kraemer; Jacques Felblinger (IEEE Trans. Biomed. Eng., 2010)

De l'Apprentissage Statistique pour le Contrôle Optimal et le Traitement du Signal. - Olivier Pietquin (2011)

Parametric value function approximation: A unified view. - Matthieu Geist; Olivier Pietquin (ADPRL, 2011)

Dynamic neural field optimization using the unscented Kalman filter. - Jérémy Fix; Matthieu Geist; Olivier Pietquin; Hervé Frezza-Buet (CCMB, 2011)

Batch reinforcement learning for optimizing longitudinal driving assistance strategies. - Olivier Pietquin; Fabio Tango; Raghav Aras (CIVTS, 2011)

Single-trial P300 detection with Kalman filtering and SVMs. - Lucie Daubigney; Olivier Pietquin (ESANN, 2011)

Batch, Off-Policy and Model-Free Apprenticeship Learning. - Edouard Klein; Matthieu Geist; Olivier Pietquin (EWRL, 2011)

Automation Effects on Driver's Behaviour When Integrating a PADAS and a Distraction Classifier. - Fabio Tango; Luca Minin; Raghav Aras; Olivier Pietquin (HCI (17), 2011)

A Non-parametric Approach to Approximate Dynamic Programming. - Hadrien Glaude; Fadi Akrimi; Matthieu Geist; Olivier Pietquin (ICMLA (1), 2011)

Sample Efficient On-Line Learning of Optimal Dialogue Policies with Kalman Temporal Differences. - Olivier Pietquin; Matthieu Geist; Senthilkumar Chandramohan (IJCAI, 2011)

Training a BN-based user model for dialogue simulation with missing data. - Stéphane Rossignol; Olivier Pietquin; Michel Ianotto (IJCNLP, 2011)

User Simulation in Dialogue Systems Using Inverse Reinforcement Learning. - Senthilkumar Chandramohan; Matthieu Geist; Fabrice Lefèvre; Olivier Pietquin (INTERSPEECH, 2011)

Uncertainty Management for On-Line Optimisation of a POMDP-Based Large-Scale Spoken Dialogue System. - Lucie Daubigney; Milica Gasic; Senthilkumar Chandramohan; Matthieu Geist; Olivier Pietquin; Steve J. Young (INTERSPEECH, 2011)

Optimization of a tutoring system from a fixed set of data. - Olivier Pietquin; Lucie Daubigney; Matthieu Geist (SLaTE, 2011)

Managing Uncertainty within KTD. - Matthieu Geist; Olivier Pietquin (Active Learning and Experimental Design @ AISTATS, 2011)

Functional Segmentation of Renal DCE-MRI Sequences Using Vector Quantization Algorithms. - Beatrice Chevaillier; Damien Mandry; Jean-Luc Collette; Michel Claudon; Marie-Agnès Galloy; Olivier Pietquin (Neural Process. Lett., 2011)

Introduction to special issue on machine learning for adaptivity in spoken dialogue systems. - Oliver Lemon; Olivier Pietquin (ACM Trans. Speech Lang. Process., 2011)

Sample-efficient batch reinforcement learning for dialogue management optimization. - Olivier Pietquin; Matthieu Geist; Senthilkumar Chandramohan; Hervé Frezza-Buet (ACM Trans. Speech Lang. Process., 2011)

Behavior Specific User Simulation in Spoken Dialogue Systems. - Senthilkumar Chandramohan; Matthieu Geist; Fabrice Lefèvre; Olivier Pietquin (ITG Conference on Speech Communication, 2012)

A Reinforcement Learning Approach to Optimize the longitudinal Behavior of a Partial Autonomous Driving Assistance System. - Olivier Pietquin; Fabio Tango (ECAI, 2012)

Clustering behaviors of Spoken Dialogue Systems users. - Senthilkumar Chandramohan; Matthieu Geist; Fabrice Lefèvre; Olivier Pietquin (ICASSP, 2012)

Off-policy learning in large-scale POMDP-based dialogue systems. - Lucie Daubigney; Matthieu Geist; Olivier Pietquin (ICASSP, 2012)

Co-adaptation in Spoken Dialogue Systems. - Senthilkumar Chandramohan; Matthieu Geist; Fabrice Lefèvre; Olivier Pietquin (IWSDS, 2012)

Statistical User Simulation for Spoken Dialogue Systems: What for, Which Data, Which Future? - Olivier Pietquin (SDCTD@NAACL-HLT, 2012)

Inverse Reinforcement Learning through Structured Classification. - Edouard Klein; Matthieu Geist; Bilal Piot; Olivier Pietquin (NIPS, 2012)

Reward Function Learning for Dialogue Management. - Layla El Asri; Romain Laroche; Olivier Pietquin (STAIRS, 2012)

Optimisation d'un tuteur intelligent à partir d'un jeu de données fixé (Optimization of a tutoring system from a fixed set of data) [in French]. - Lucie Daubigney; Matthieu Geist; Olivier Pietquin (JEP-TALN-RECITAL 2012, 2012)

A Comprehensive Reinforcement Learning Framework for Dialogue Management Optimization. - Lucie Daubigney; Matthieu Geist; Senthilkumar Chandramohan; Olivier Pietquin (IEEE J. Sel. Top. Signal Process., 2012)

Introduction to the Issue on Advances in Spoken Dialogue Systems and Mobile Interface. - Jason D. Williams; Kai Yu 004; Brahim Chaib-draa; Oliver Lemon; Roberto Pieraccini; Olivier Pietquin; Pascal Poupart; Steve J. Young (IEEE J. Sel. Top. Signal Process., 2012)

Laugh-aware virtual agent and its impact on user amusement. - Radoslaw Niewiadomski; Jennifer Hofmann; Jérôme Urbain; Tracey Platt; Johannes Wagner 001; Bilal Piot; Hüseyin Çakmak; Sathish Pammi; Tobias Baur 001; Stéphane Dupont; Matthieu Geist; Florian Lingenfelser; et al. (AAMAS, 2013)

Random projections: A remedy for overfitting issues in time series prediction with echo state networks. - Lucie Daubigney; Matthieu Geist; Olivier Pietquin (ICASSP, 2013)

Laugh When You're Winning. - Maurizio Mancini; Laurent Ach; Emeline Bantegnie; Tobias Baur 001; Nadia Berthouze; Debajyoti Datta; Yu Ding 001; Stéphane Dupont; Harry J. Griffin; Florian Lingenfelser; Radoslaw Niewiadomski; Catherine Pelachaud; et al. (eNTERFACE, 2013)

Inverse reinforcement learning for interactive systems. - Olivier Pietquin (MLIS@IJCAI, 2013)

Particle swarm optimisation of spoken dialogue system strategies. - Lucie Daubigney; Matthieu Geist; Olivier Pietquin (INTERSPEECH, 2013)

A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning. - Edouard Klein; Bilal Piot; Matthieu Geist; Olivier Pietquin (ECML/PKDD (1), 2013)

Learning from Demonstrations: Is It Worth Estimating a Reward Function? - Bilal Piot; Matthieu Geist; Olivier Pietquin (ECML/PKDD (1), 2013)

Model-free POMDP optimisation of tutoring systems with echo-state networks. - Lucie Daubigney; Matthieu Geist; Olivier Pietquin (SIGDIAL Conference, 2013)

Reward Shaping for Statistical Optimisation of Dialogue Management. - Layla El Asri; Romain Laroche; Olivier Pietquin (SLSP, 2013)

A survey on metrics for the evaluation of user simulations. - Olivier Pietquin; Helen F. Hastie (Knowl. Eng. Rev., 2013)

Classification structurée pour l'apprentissage par renforcement inverse. - Edouard Klein; Bilal Piot; Matthieu Geist; Olivier Pietquin (Rev. d'Intelligence Artif., 2013)

Algorithmic Survey of Parametric Value Function Approximation. - Matthieu Geist; Olivier Pietquin (IEEE Trans. Neural Networks Learn. Syst., 2013)

Active learning for classification: An optimistic approach. - Timothé Collet; Olivier Pietquin (ADPRL, 2014)

Subspace identification for predictive state representation by nuclear norm minimization. - Hadrien Glaude; Olivier Pietquin; Cyrille Enderli (ADPRL, 2014)

Boosted and reward-regularized classification for apprenticeship learning. - Bilal Piot; Matthieu Geist; Olivier Pietquin (AAMAS, 2014)

Ordinal regression for interaction quality prediction. - Layla El Asri; Hatim Khouzaimi; Romain Laroche; Olivier Pietquin (ICASSP, 2014)

Predicting when to laugh with structured classification. - Bilal Piot; Olivier Pietquin; Matthieu Geist (INTERSPEECH, 2014)

NASTIA: Negotiating Appointment Setting Interface. - Layla El Asri; Rémi Lemonnier; Romain Laroche; Olivier Pietquin; Hatim Khouzaimi (LREC, 2014)

DINASTI: Dialogues with a Negotiating Appointment Setting Interface. - Layla El Asri; Romain Laroche; Olivier Pietquin (LREC, 2014)

Difference of Convex Functions Programming for Reinforcement Learning. - Bilal Piot; Matthieu Geist; Olivier Pietquin (NIPS, 2014)

Boosted Bellman Residual Minimization Handling Expert Demonstrations. - Bilal Piot; Matthieu Geist; Olivier Pietquin (ECML/PKDD (2), 2014)

Spectral learning with non negative probabilities for finite state automaton. - Hadrien Glaude; Cyrille Enderli; Olivier Pietquin (ASRU, 2015)

Proceedings of the 4th Workshop on Machine Learning for Interactive Systems (MLIS-2015). - Heriberto Cuayáhuitl; Nina Dethlefs; Lutz Frommberger; Martijn van Otterlo; Olivier Pietquin (MLIS@ICML, 2015)

Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games. - Julien Pérolat; Bruno Scherrer; Bilal Piot; Olivier Pietquin (ICML, 2015)

Imitation Learning Applied to Embodied Conversational Agents. - Bilal Piot; Olivier Pietquin; Matthieu Geist (MLIS@ICML, 2015)

Optimism in Active Learning with Gaussian Processes. - Timothé Collet; Olivier Pietquin (ICONIP (2), 2015)

Non-negative Spectral Learning for Linear Sequential Systems. - Hadrien Glaude; Cyrille Enderli; Olivier Pietquin (ICONIP (2), 2015)

Inverse Reinforcement Learning in Relational Domains. - Thibaut Munzer; Bilal Piot; Matthieu Geist; Olivier Pietquin; Manuel Lopes 001 (IJCAI, 2015)

Learning of scanning strategies for electronic support using predictive state representations. - Hadrien Glaude; Cyrille Enderli; Jean-François Grandin; Olivier Pietquin (MLSP, 2015)

Human-Machine Dialogue as a Stochastic Game. - Merwan Barlier; Julien Pérolat; Romain Laroche; Olivier Pietquin (SIGDIAL Conference, 2015)

Bayesian Credible Intervals for Online and Active Learning of Classification Trees. - Timothé Collet; Olivier Pietquin (SSCI, 2015)

Optimism in Active Learning. - Timothé Collet; Olivier Pietquin (Comput. Intell. Neurosci., 2015)

On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games. - Julien Pérolat; Bilal Piot; Bruno Scherrer; Olivier Pietquin (AISTATS, 2016)

Score-based Inverse Reinforcement Learning. - Layla El Asri; Bilal Piot; Matthieu Geist; Romain Laroche; Olivier Pietquin (AAMAS, 2016)

PAC learning of Probabilistic Automaton based on the Method of Moments. - Hadrien Glaude; Olivier Pietquin (ICML, 2016)

Softened Approximate Policy Iteration for Markov Games. - Julien Pérolat; Bilal Piot; Matthieu Geist; Bruno Scherrer; Olivier Pietquin (ICML, 2016)

A Stochastic Model for Computer-Aided Human-Human Dialogue. - Merwan Barlier; Romain Laroche; Olivier Pietquin (INTERSPEECH, 2016)

Compact and Interpretable Dialogue State Representation with Genetic Sparse Distributed Memory. - Layla El Asri; Romain Laroche; Olivier Pietquin (IWSDS, 2016)

MultiVec: a Multilingual and Multilevel Representation Learning Toolkit for NLP. - Alexandre Berard; Christophe Servan; Olivier Pietquin; Laurent Besacier (LREC, 2016)

Learning dialogue dynamics with the method of moments. - Merwan Barlier; Romain Laroche; Olivier Pietquin (SLT, 2016)

Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation. - Alexandre Berard; Olivier Pietquin; Christophe Servan; Laurent Besacier (CoRR, 2016)

Should one minimize the expected Bellman residual or maximize the mean value? - Matthieu Geist; Bilal Piot; Olivier Pietquin (CoRR, 2016)

Difference of Convex Functions Programming Applied to Control with Expert Data. - Bilal Piot; Matthieu Geist; Olivier Pietquin (CoRR, 2016)

Laughter Research: A Review of the ILHAIRE Project. - Stéphane Dupont; Hüseyin Çakmak; William Curran; Thierry Dutoit; Jennifer Hofmann; Gary McKeown; Olivier Pietquin; Tracey Platt; Willibald Ruch; Jérôme Urbain (Toward Robotic Socially Believable Behaving Systems (I), 2016)

Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. - Julien Pérolat; Florian Strub; Bilal Piot; Olivier Pietquin (AISTATS, 2017)

GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. - Harm de Vries; Florian Strub; Sarath Chandar; Olivier Pietquin; Hugo Larochelle; Aaron C. Courville (CVPR, 2017)

End-to-end optimization of goal-driven and visually grounded dialogue systems. - Florian Strub; Harm de Vries; Jérémie Mary; Bilal Piot; Aaron C. Courville; Olivier Pietquin (IJCAI, 2017)

Is the Bellman residual a bad proxy? - Matthieu Geist; Bilal Piot; Olivier Pietquin (NIPS, 2017)

Modulating early visual processing by language. - Harm de Vries; Florian Strub; Jérémie Mary; Hugo Larochelle; Olivier Pietquin; Aaron C. Courville (NIPS, 2017)

LIG-CRIStAL Submission for the WMT 2017 Automatic Post-Editing Task. - Alexandre Berard; Laurent Besacier; Olivier Pietquin (WMT, 2017)

LIG-CRIStAL System for the WMT17 Automatic Post-Editing Task. - Alexandre Berard; Olivier Pietquin; Laurent Besacier (CoRR, 2017)

Observational Learning by Reinforcement Learning. - Diana Borsa; Bilal Piot; Rémi Munos; Olivier Pietquin (CoRR, 2017)

Noisy Networks for Exploration. - Meire Fortunato; Mohammad Gheshlaghi Azar; Bilal Piot; Jacob Menick; Ian Osband; Alex Graves; Vlad Mnih; Rémi Munos; Demis Hassabis; Olivier Pietquin; Charles Blundell; Shane Legg (CoRR, 2017)

Learning from Demonstrations for Real World Reinforcement Learning. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Andrew Sendonaris; Gabriel Dulac-Arnold; Ian Osband; John P. Agapiou; Joel Z. Leibo; Audrunas Gruslys (CoRR, 2017)

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. - Matej Vecerík; Todd Hester; Jonathan Scholz; Fumin Wang; Olivier Pietquin; Bilal Piot; Nicolas Heess; Thomas Rothörl; Thomas Lampe; Martin A. Riedmiller (CoRR, 2017)

Bridging the Gap Between Imitation Learning and Inverse Reinforcement Learning. - Bilal Piot; Matthieu Geist; Olivier Pietquin (IEEE Trans. Neural Networks Learn. Syst., 2017)

Deep learning for multisensorial and multimodal interaction. - Gil Keren; Amr El-Desoky Mousa; Olivier Pietquin; Stefanos Zafeiriou; Björn W. Schuller (The Handbook of Multimodal-Multisensor Interfaces, Volume 2 (2), 2018)

Deep Q-learning From Demonstrations. - Todd Hester; Matej Vecerík; Olivier Pietquin; Marc Lanctot; Tom Schaul; Bilal Piot; Dan Horgan; John Quan; Andrew Sendonaris; Ian Osband; Gabriel Dulac-Arnold; John P. Agapiou; et al. (AAAI, 2018)

Actor-Critic Fictitious Play in Simultaneous Move Multistage Games. - Julien Pérolat; Bilal Piot; Olivier Pietquin (AISTATS, 2018)

Training Dialogue Systems With Human Advice. - Merwan Barlier; Romain Laroche; Olivier Pietquin (AAMAS, 2018)

Visual Reasoning with Multi-hop Feature Modulation. - Florian Strub; Mathieu Seurin; Ethan Perez; Harm de Vries; Jérémie Mary; Philippe Preux; Aaron C. Courville; Olivier Pietquin (ECCV (5), 2018)

End-to-End Automatic Speech Translation of Audiobooks. - Alexandre Berard; Laurent Besacier; Ali Can Kocabiyikoglu; Olivier Pietquin (ICASSP, 2018)

Noisy Networks For Exploration. - Meire Fortunato; Mohammad Gheshlaghi Azar; Bilal Piot; Jacob Menick; Matteo Hessel; Ian Osband; Alex Graves; Volodymyr Mnih; Rémi Munos; Demis Hassabis; Olivier Pietquin; Charles Blundell; et al. (ICLR (Poster), 2018)

Observe and Look Further: Achieving Consistent Performance on Atari. - Tobias Pohlen; Bilal Piot; Todd Hester; Mohammad Gheshlaghi Azar; Dan Horgan; David Budden; Gabriel Barth-Maron; Hado van Hasselt; John Quan; Mel Vecerík; Matteo Hessel; Rémi Munos; et al. (CoRR, 2018)

Playing the Game of Universal Adversarial Perturbations. - Julien Pérolat; Mateusz Malinowski; Bilal Piot; Olivier Pietquin (CoRR, 2018)

Observational Learning by Reinforcement Learning. - Diana Borsa; Nicolas Heess; Bilal Piot; Siqi Liu 002; Leonard Hasenclever; Rémi Munos; Olivier Pietquin (AAMAS, 2019)

A Theory of Regularized Markov Decision Processes. - Matthieu Geist; Bruno Scherrer; Olivier Pietquin (ICML, 2019)

Learning from a Learner. - Alexis Jacq; Matthieu Geist; Ana Paiva 001; Olivier Pietquin (ICML, 2019)

Budgeted Reinforcement Learning in Continuous State Space. - Nicolas Carrara; Edouard Leurent; Romain Laroche; Tanguy Urvoy; Odalric-Ambrym Maillard; Olivier Pietquin (NeurIPS, 2019)

Self-Educated Language Agent with Hindsight Experience Replay for Instruction Following. - Geoffrey Cideron; Mathieu Seurin; Florian Strub; Olivier Pietquin (ViGIL@NeurIPS, 2019)

Scaling up budgeted reinforcement learning. - Nicolas Carrara; Edouard Leurent; Romain Laroche; Tanguy Urvoy; Odalric-Ambrym Maillard; Olivier Pietquin (CoRR, 2019)

Targeted Attacks on Deep Reinforcement Learning Agents through Adversarial Observations. - Léonard Hussenot; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

MULEX: Disentangling Exploitation from Exploration in Deep RL. - Lucas Beyer; Damien Vincent; Olivier Teboul; Sylvain Gelly; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

Approximate Fictitious Play for Mean Field Games. - Romuald Elie; Julien Pérolat; Mathieu Laurière; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

Credit Assignment as a Proxy for Transfer in Reinforcement Learning. - Johan Ferret; Raphaël Marinier; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

"I'm sorry Dave, I'm afraid I can't do that" Deep Q-learning from forbidden action. - Mathieu Seurin; Philippe Preux; Olivier Pietquin (CoRR, 2019)

On Connections between Constrained Optimization and Reinforcement Learning. - Nino Vieillard; Olivier Pietquin; Matthieu Geist (CoRR, 2019)

Reinforcement Learning. - Olivier Buffet; Olivier Pietquin; Paul Weng (A Guided Tour of Artificial Intelligence Research (1) (I), 2020)

On the Convergence of Model Free Learning in Mean Field Games. - Romuald Elie; Julien Pérolat; Mathieu Laurière; Matthieu Geist; Olivier Pietquin (AAAI, 2020)

Deep Conservative Policy Iteration. - Nino Vieillard; Olivier Pietquin; Matthieu Geist (AAAI, 2020)

Foolproof Cooperative Learning. - Alexis Jacq; Julien Pérolat; Matthieu Geist; Olivier Pietquin (ACML, 2020)

Momentum in Reinforcement Learning. - Nino Vieillard; Bruno Scherrer; Olivier Pietquin; Matthieu Geist (AISTATS, 2020)

CopyCAT: : Taking Control of Neural Policies with Constant Attacks. - Léonard Hussenot; Matthieu Geist; Olivier Pietquin (AAMAS, 2020)

Supervised Seeded Iterated Learning for Interactive Language Learning. - Yuchen Lu; Soumye Singhal; Florian Strub; Olivier Pietquin; Aaron C. Courville (EMNLP (1), 2020)

Countering Language Drift with Seeded Iterated Learning. - Yuchen Lu; Soumye Singhal; Florian Strub; Aaron C. Courville; Olivier Pietquin (ICML, 2020)

Self-Attentional Credit Assignment for Transfer in Reinforcement Learning. - Johan Ferret; Raphaël Marinier; Matthieu Geist; Olivier Pietquin (IJCAI, 2020)

"I'm Sorry Dave, I'm Afraid I Can't Do That" Deep Q-Learning from Forbidden Actions. - Mathieu Seurin; Philippe Preux; Olivier Pietquin (IJCNN, 2020)

A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning. - Mathieu Seurin; Florian Strub; Philippe Preux; Olivier Pietquin (INTERSPEECH, 2020)

Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. - Sarah Perrin; Julien Pérolat; Mathieu Laurière; Matthieu Geist; Romuald Elie; Olivier Pietquin (NeurIPS, 2020)

Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning. - Nino Vieillard; Tadashi Kozuno; Bruno Scherrer; Olivier Pietquin; Rémi Munos; Matthieu Geist (NeurIPS, 2020)

Munchausen Reinforcement Learning. - Nino Vieillard; Olivier Pietquin; Matthieu Geist (NeurIPS, 2020)

HIGhER: Improving instruction following with Hindsight Generation for Experience Replay. - Geoffrey Cideron; Mathieu Seurin; Florian Strub; Olivier Pietquin (SSCI, 2020)

Leverage the Average: an Analysis of Regularization in RL. - Nino Vieillard; Tadashi Kozuno; Bruno Scherrer; Olivier Pietquin; Rémi Munos; Matthieu Geist (CoRR, 2020)

Reinforcement Learning. - Olivier Buffet; Olivier Pietquin; Paul Weng (CoRR, 2020)

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study. - Marcin Andrychowicz; Anton Raichuk; Piotr Stanczyk; Manu Orsini; Sertan Girgin; Raphaël Marinier; Léonard Hussenot; Matthieu Geist; Olivier Pietquin; Marcin Michalski; Sylvain Gelly; Olivier Bachem (CoRR, 2020)

The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction. - Alice Martin 001; Charles Ollion; Florian Strub; Sylvain Le Corff; Olivier Pietquin (CoRR, 2020)

Self-Imitation Advantage Learning. - Johan Ferret; Olivier Pietquin; Matthieu Geist (AAMAS, 2021)

Show Me the Way: Intrinsic Motivation from Demonstrations. - Léonard Hussenot; Robert Dadashi; Matthieu Geist; Olivier Pietquin (AAMAS, 2021)

Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering. - Aaqib Saeed; David Grangier; Olivier Pietquin; Neil Zeghidour (ICASSP, 2021)

What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study. - Marcin Andrychowicz; Anton Raichuk; Piotr Stanczyk; Manu Orsini; Sertan Girgin; Raphaël Marinier; Léonard Hussenot; Matthieu Geist; Olivier Pietquin; Marcin Michalski; Sylvain Gelly; Olivier Bachem (ICLR, 2021)

Primal Wasserstein Imitation Learning. - Robert Dadashi; Léonard Hussenot; Matthieu Geist; Olivier Pietquin (ICLR, 2021)

Adversarially Guided Actor-Critic. - Yannis Flet-Berliac; Johan Ferret; Olivier Pietquin; Philippe Preux; Matthieu Geist (ICLR, 2021)

Offline Reinforcement Learning with Pseudometric Learning. - Robert Dadashi; Shideh Rezaeifar; Nino Vieillard; Léonard Hussenot; Olivier Pietquin; Matthieu Geist (ICML, 2021)

Hyperparameter Selection for Imitation Learning. - Léonard Hussenot; Marcin Andrychowicz; Damien Vincent; Robert Dadashi; Anton Raichuk; Sabela Ramos; Nikola Momchev; Sertan Girgin; Raphaël Marinier; Lukasz Stafiniak; Manu Orsini; Olivier Bachem; et al. (ICML, 2021)

Mean Field Games Flock! The Reinforcement Learning Way. - Sarah Perrin; Mathieu Laurière; Julien Pérolat; Matthieu Geist; Romuald Élie; Olivier Pietquin (IJCAI, 2021)

Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness. - Mathieu Seurin; Florian Strub; Philippe Preux; Olivier Pietquin (IJCAI, 2021)

There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning. - Nathan Grinsztajn; Johan Ferret; Olivier Pietquin; Philippe Preux; Matthieu Geist (NeurIPS, 2021)

What Matters for Adversarial Imitation Learning? - Manu Orsini; Anton Raichuk; Léonard Hussenot; Damien Vincent; Robert Dadashi; Sertan Girgin; Matthieu Geist; Olivier Bachem; Olivier Pietquin; Marcin Andrychowicz (NeurIPS, 2021)

Scaling up Mean Field Games with Online Mirror Descent. - Julien Pérolat; Sarah Perrin; Romuald Elie; Mathieu Laurière; Georgios Piliouras; Matthieu Geist; Karl Tuyls; Olivier Pietquin (CoRR, 2021)

Learning Natural Language Generation from Scratch. - Alice Martin 001; Guillaume Quispe; Charles Ollion; Sylvain Le Corff; Florian Strub; Olivier Pietquin (CoRR, 2021)

RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning. - Sabela Ramos; Sertan Girgin; Léonard Hussenot; Damien Vincent; Hanna Yakubovich; Daniel Toyama; Anita Gergely; Piotr Stanczyk; Raphaël Marinier; Jeremiah Harmsen; Olivier Pietquin; Nikola Momchev (CoRR, 2021)

Generalization in Mean Field Games by Learning Master Policies. - Sarah Perrin; Mathieu Laurière; Julien Pérolat; Romuald Élie; Matthieu Geist; Olivier Pietquin (AAAI, 2022)

Offline Reinforcement Learning as Anti-exploration. - Shideh Rezaeifar; Robert Dadashi; Nino Vieillard; Léonard Hussenot; Olivier Bachem; Olivier Pietquin; Matthieu Geist (AAAI, 2022)

Implicitly Regularized RL with Implicit Q-values. - Nino Vieillard; Marcin Andrychowicz; Anton Raichuk; Olivier Pietquin; Matthieu Geist (AISTATS, 2022)

Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. - Theophile Cabannes; Mathieu Laurière; Julien Pérolat; Raphaël Marinier; Sertan Girgin; Sarah Perrin; Olivier Pietquin; Alexandre M. Bayen; Eric Goubault; Romuald Elie (AAMAS, 2022)

Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. - Matthieu Geist; Julien Pérolat; Mathieu Laurière; Romuald Elie; Sarah Perrin; Olivier Bachem; Rémi Munos; Olivier Pietquin (AAMAS, 2022)

Lazy-MDPs: Towards Interpretable RL by Learning When to Act. - Alexis Jacq; Johan Ferret; Olivier Pietquin; Matthieu Geist (AAMAS, 2022)

Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. - Paul Muller; Mark Rowland 001; Romuald Elie; Georgios Piliouras; Julien Pérolat; Mathieu Laurière; Raphaël Marinier; Olivier Pietquin; Karl Tuyls (AAMAS, 2022)

Scaling Mean Field Games by Online Mirror Descent. - Julien Pérolat; Sarah Perrin; Romuald Elie; Mathieu Laurière; Georgios Piliouras; Matthieu Geist; Karl Tuyls; Olivier Pietquin (AAMAS, 2022)

On the role of population heterogeneity in emergent communication. - Mathieu Rita; Florian Strub; Jean-Bastien Grill; Olivier Pietquin; Emmanuel Dupoux (ICLR, 2022)

Continuous Control with Action Quantization from Demonstrations. - Robert Dadashi; Léonard Hussenot; Damien Vincent; Sertan Girgin; Anton Raichuk; Matthieu Geist; Olivier Pietquin (ICML, 2022)

Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. - Mathieu Laurière; Sarah Perrin; Sertan Girgin; Paul Muller; Ayush Jain; Theophile Cabannes; Georgios Piliouras; Julien Pérolat; Romuald Elie; Olivier Pietquin; Matthieu Geist (ICML, 2022)

Learning Natural Language Generation with Truncated Reinforcement Learning. - Alice Martin 001; Guillaume Quispe; Charles Ollion; Sylvain Le Corff; Florian Strub; Olivier Pietquin (NAACL-HLT, 2022)

Emergent Communication: Generalization and Overfitting in Lewis Games. - Mathieu Rita; Corentin Tallec; Paul Michel; Jean-Bastien Grill; Olivier Pietquin; Emmanuel Dupoux; Florian Strub (NeurIPS, 2022)

Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act. - Alexis Jacq; Johan Ferret; Olivier Pietquin; Matthieu Geist (CoRR, 2022)

Learning Mean Field Games: A Survey. - Mathieu Laurière; Sarah Perrin; Matthieu Geist; Olivier Pietquin (CoRR, 2022)

KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal. - Tadashi Kozuno; Wenhao Yang; Nino Vieillard; Toshinori Kitamura; Yunhao Tang; Jincheng Mei; Pierre Ménard; Mohammad Gheshlaghi Azar; Michal Valko; Rémi Munos; Olivier Pietquin; Matthieu Geist; et al. (CoRR, 2022)

Learning Correlated Equilibria in Mean-Field Games. - Paul Muller; Romuald Elie; Mark Rowland 001; Mathieu Laurière; Julien Pérolat; Sarah Perrin; Matthieu Geist; Georgios Piliouras; Olivier Pietquin; Karl Tuyls (CoRR, 2022)

AudioLM: a Language Modeling Approach to Audio Generation. - Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matthew Sharifi; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour (CoRR, 2022)

vec2text with Round-Trip Translations. - Geoffrey Cideron; Sertan Girgin; Anton Raichuk; Olivier Pietquin; Olivier Bachem; Léonard Hussenot (CoRR, 2022)

C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining. - Alexis Jacq; Manu Orsini; Gabriel Dulac-Arnold; Olivier Pietquin; Matthieu Geist; Olivier Bachem (CoRR, 2022)

Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. - Paul Roit; Johan Ferret; Lior Shani; Roee Aharoni; Geoffrey Cideron; Robert Dadashi; Matthieu Geist; Sertan Girgin; Léonard Hussenot; Orgad Keller; Nikola Momchev; Sabela Ramos Garea; et al. (ACL (1), 2023)

Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. - Toshinori Kitamura; Tadashi Kozuno; Yunhao Tang; Nino Vieillard; Michal Valko; Wenhao Yang; Jincheng Mei; Pierre Ménard; Mohammad Gheshlaghi Azar; Rémi Munos; Olivier Pietquin; Matthieu Geist; et al. (ICML, 2023)

On Imitation in Mean-field Games. - Giorgia Ramponi; Pavel Kolev; Olivier Pietquin; Niao He; Mathieu Laurière; Matthieu Geist (NeurIPS, 2023)

SingSong: Generating musical accompaniments from singing. - Chris Donahue; Antoine Caillon; Adam Roberts; Ethan Manilow; Philippe Esling; Andrea Agostinelli; Mauro Verzetti; Ian Simon; Olivier Pietquin; Neil Zeghidour; Jesse H. Engel (CoRR, 2023)

Get Back Here: Robust Imitation by Return-to-Distribution Planning. - Geoffrey Cideron; Baruch Tabanpour; Sebastian Curi; Sertan Girgin; Léonard Hussenot; Gabriel Dulac-Arnold; Matthieu Geist; Olivier Pietquin; Robert Dadashi (CoRR, 2023)

Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision. - Eugene Kharitonov; Damien Vincent; Zalán Borsos; Raphaël Marinier; Sertan Girgin; Olivier Pietquin; Matt Sharifi; Marco Tagliasacchi; Neil Zeghidour (Trans. Assoc. Comput. Linguistics, 2023)

AudioLM: A Language Modeling Approach to Audio Generation. - Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matthew Sharifi; Dominik Roblek; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour (IEEE ACM Trans. Audio Speech Lang. Process., 2023)

Learning Discrete-Time Major-Minor Mean Field Games. - Kai Cui 001; Gökçe Dayanikli; Mathieu Laurière; Matthieu Geist; Olivier Pietquin; Heinz Koeppl (AAAI, 2024)

Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs. - Arash Ahmadian; Chris Cremer; Matthias Gallé; Marzieh Fadaee; Julia Kreutzer; Olivier Pietquin; Ahmet Üstün; Sara Hooker (ACL (1), 2024)

Countering Reward Over-Optimization in LLM with Demonstration-Guided Reinforcement Learning. - Mathieu Rita; Florian Strub; Rahma Chaabouni 001; Paul Michel; Emmanuel Dupoux; Olivier Pietquin (ACL (Findings), 2024)

Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. - Zida Wu; Mathieu Laurière; Samuel Jia Cong Chua; Matthieu Geist; Olivier Pietquin; Ankur Mehta (AAMAS, 2024)

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. - Yannis Flet-Berliac; Nathan Grinsztajn; Florian Strub; Eugene Choi; Bill Wu; Chris Cremer; Arash Ahmadian; Yash Chandak; Mohammad Gheshlaghi Azar; Olivier Pietquin; Matthieu Geist (EMNLP, 2024)

MusicRL: Aligning Music Generation to Human Preferences. - Geoffrey Cideron; Sertan Girgin; Mauro Verzetti; Damien Vincent; Matej Kastelic; Zalán Borsos; Brian McWilliams; Victor Ungureanu; Olivier Bachem; Olivier Pietquin; Matthieu Geist; Léonard Hussenot; et al. (ICML, 2024)

Language Evolution with Deep Learning. - Mathieu Rita; Paul Michel; Rahma Chaabouni 001; Olivier Pietquin; Emmanuel Dupoux; Florian Strub (CoRR, 2024)

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. - Yannis Flet-Berliac; Nathan Grinsztajn; Florian Strub; Eugene Choi; Chris Cremer; Arash Ahmadian; Yash Chandak; Mohammad Gheshlaghi Azar; Olivier Pietquin; Matthieu Geist (CoRR, 2024)

Averaging log-likelihoods in direct alignment. - Nathan Grinsztajn; Yannis Flet-Berliac; Mohammad Gheshlaghi Azar; Florian Strub; Bill Wu; Eugene Choi; Chris Cremer; Arash Ahmadian; Yash Chandak; Olivier Pietquin; Matthieu Geist (CoRR, 2024)

Biodenoising: Animal Vocalization Denoising without Access to Clean Data. - Marius Miron; Sara Keen; Jen-Yu Liu; Benjamin Hoffman; Masato Hagiwara; Olivier Pietquin; Felix Effenberger; Maddie Cusimano (ICASSP, 2025)

Self-Improving Robust Preference Optimization. - Eugene Choi; Arash Ahmadian; Matthieu Geist; Olivier Pietquin; Mohammad Gheshlaghi Azar (ICLR, 2025)

NatureLM-audio: an Audio-Language Foundation Model for Bioacoustics. - David Robinson; Marius Miron; Masato Hagiwara; Olivier Pietquin (ICLR, 2025)

Synthetic data enables context-aware bioacoustic sound event detection. - Benjamin Hoffman; David Robinson; Marius Miron; Vittorio Baglione; Daniela Canestrari; Damian Elias; Eva Trapote; Olivier Pietquin (CoRR, 2025)

Robust detection of overlapping bioacoustic sound events. - Louis Mahon; Benjamin Hoffman; Logan S. James; Maddie Cusimano; Masato Hagiwara; Sarah C. Woolley; Olivier Pietquin (CoRR, 2025)

ShiQ: Bringing back Bellman to LLMs. - Pierre Clavier; Nathan Grinsztajn; Raphaël Avalos; Yannis Flet-Berliac; Irem Ergün; Omar Darwiche Domingues; Eugene Tarassov; Olivier Pietquin; Pierre H. Richemond; Florian Strub; Matthieu Geist (CoRR, 2025)

What Matters for Bioacoustic Encoding. - Marius Miron; David Robinson; Milad Alizadeh; Ellen Gilsenan-McMahon; Gagan Narula; Emmanuel Chemla; Maddie Cusimano; Felix Effenberger; Masato Hagiwara; Benjamin Hoffman; Sara Keen; Diane Kim; et al. (CoRR, 2025)