Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDOlivier Pietquin
Person information
- affiliation: Google DeepMind
- affiliation: University Lille 1, France
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[i46]Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist:
Adversarially Guided Actor-Critic. CoRR abs/2102.04376 (2021)- [i45]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 abs/2103.00623 (2021) - [i44]Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist:
Offline Reinforcement Learning with Pseudometric Learning. CoRR abs/2103.01948 (2021) - 2020
- [c118]Nino Vieillard, Olivier Pietquin, Matthieu Geist:
Deep Conservative Policy Iteration. AAAI 2020: 6070-6077 - [c117]Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin:
On the Convergence of Model Free Learning in Mean Field Games. AAAI 2020: 7143-7150 - [c116]Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin:
Foolproof Cooperative Learning. ACML 2020: 401-416 - [c115]Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist:
Momentum in Reinforcement Learning. AISTATS 2020: 2529-2538 - [c114]Léonard Hussenot, Matthieu Geist, Olivier Pietquin:
CopyCAT: : Taking Control of Neural Policies with Constant Attacks. AAMAS 2020: 548-556 - [c113]Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville:
Supervised Seeded Iterated Learning for Interactive Language Learning. EMNLP (1) 2020: 3962-3970 - [c112]Yuchen Lu, Soumye Singhal, Florian Strub, Aaron C. Courville, Olivier Pietquin:
Countering Language Drift with Seeded Iterated Learning. ICML 2020: 6437-6447 - [c111]Johan Ferret, Raphaël Marinier, Matthieu Geist, Olivier Pietquin:
Self-Attentional Credit Assignment for Transfer in Reinforcement Learning. IJCAI 2020: 2655-2661 - [c110]Mathieu Seurin, Philippe Preux, Olivier Pietquin:
"I'm Sorry Dave, I'm Afraid I Can't Do That" Deep Q-Learning from Forbidden Actions. IJCNN 2020: 1-8 - [c109]Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin:
A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning. INTERSPEECH 2020: 4323-4327 - [c108]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 - [c107]Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist:
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning. NeurIPS 2020 - [c106]Nino Vieillard, Olivier Pietquin, Matthieu Geist:
Munchausen Reinforcement Learning. NeurIPS 2020 - [c105]Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin:
HIGhER: Improving instruction following with Hindsight Generation for Experience Replay. SSCI 2020: 225-232 - [e1]Olivier Pietquin, Smaranda Muresan, Vivian Chen, Casey Kennington, David Vandyke, Nina Dethlefs, Koji Inoue, Erik Ekstedt, Stefan Ultes:
Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGdial 2020, 1st virtual meeting, July 1-3, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-02-6 [contents] - [i43]Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville:
Countering Language Drift with Seeded Iterated Learning. CoRR abs/2003.12694 (2020) - [i42]Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist:
Leverage the Average: an Analysis of Regularization in RL. CoRR abs/2003.14089 (2020) - [i41]Olivier Buffer, Olivier Pietquin, Paul Weng:
Reinforcement Learning. CoRR abs/2005.14419 (2020) - [i40]Robert Dadashi, Léonard Hussenot, Matthieu Geist, Olivier Pietquin:
Primal Wasserstein Imitation Learning. CoRR abs/2006.04678 (2020) - [i39]Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem:
What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study. CoRR abs/2006.05990 (2020) - [i38]Léonard Hussenot, Robert Dadashi, Matthieu Geist, Olivier Pietquin:
Show me the Way: Intrinsic Motivation from Demonstrations. CoRR abs/2006.12917 (2020) - [i37]Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin:
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. CoRR abs/2007.03458 (2020) - [i36]Alice Martin, Charles Ollion, Florian Strub, Sylvain Le Corff, Olivier Pietquin:
The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction. CoRR abs/2007.08620 (2020) - [i35]Nino Vieillard, Olivier Pietquin, Matthieu Geist:
Munchausen Reinforcement Learning. CoRR abs/2007.14430 (2020) - [i34]Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin:
A Machine of Few Words - Interactive Speaker Recognition with Reinforcement Learning. CoRR abs/2008.03127 (2020) - [i33]Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville:
Supervised Seeded Iterated Learning for Interactive Language Learning. CoRR abs/2010.02975 (2020) - [i32]Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour:
Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering. CoRR abs/2010.13694 (2020) - [i31]Johan Ferret, Olivier Pietquin, Matthieu Geist:
Self-Imitation Advantage Learning. CoRR abs/2012.11989 (2020)
2010 – 2019
- 2019
- [c104]Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Rémi Munos, Olivier Pietquin:
Observational Learning by Reinforcement Learning. AAMAS 2019: 1117-1124 - [c103]Matthieu Geist, Bruno Scherrer, Olivier Pietquin:
A Theory of Regularized Markov Decision Processes. ICML 2019: 2160-2169 - [c102]Alexis Jacq, Matthieu Geist, Ana Paiva, Olivier Pietquin:
Learning from a Learner. ICML 2019: 2990-2999 - [c101]Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, Odalric-Ambrym Maillard, Olivier Pietquin:
Budgeted Reinforcement Learning in Continuous State Space. NeurIPS 2019: 9295-9305 - [i30]Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin:
Self-Educated Language Agent with Hindsight Experience Replay for Instruction Following. ViGIL@NeurIPS 2019 - [i29]Matthieu Geist, Bruno Scherrer, Olivier Pietquin:
A Theory of Regularized Markov Decision Processes. CoRR abs/1901.11275 (2019) - [i28]Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, Odalric-Ambrym Maillard, Olivier Pietquin:
Scaling up budgeted reinforcement learning. CoRR abs/1903.01004 (2019) - [i27]Léonard Hussenot, Matthieu Geist, Olivier Pietquin:
Targeted Attacks on Deep Reinforcement Learning Agents through Adversarial Observations. CoRR abs/1905.12282 (2019) - [i26]Nino Vieillard, Olivier Pietquin, Matthieu Geist:
Deep Conservative Policy Iteration. CoRR abs/1906.09784 (2019) - [i25]Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin:
Foolproof Cooperative Learning. CoRR abs/1906.09831 (2019) - [i24]Lucas Beyer, Damien Vincent, Olivier Teboul, Sylvain Gelly, Matthieu Geist, Olivier Pietquin:
MULEX: Disentangling Exploitation from Exploration in Deep RL. CoRR abs/1907.00868 (2019) - [i23]Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin:
Approximate Fictitious Play for Mean Field Games. CoRR abs/1907.02633 (2019) - [i22]Johan Ferret, Raphaël Marinier, Matthieu Geist, Olivier Pietquin:
Credit Assignment as a Proxy for Transfer in Reinforcement Learning. CoRR abs/1907.08027 (2019) - [i21]Mathieu Seurin, Philippe Preux, Olivier Pietquin:
"I'm sorry Dave, I'm afraid I can't do that" Deep Q-learning from forbidden action. CoRR abs/1910.02078 (2019) - [i20]Nino Vieillard, Olivier Pietquin, Matthieu Geist:
On Connections between Constrained Optimization and Reinforcement Learning. CoRR abs/1910.08476 (2019) - [i19]Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist:
Momentum in Reinforcement Learning. CoRR abs/1910.09322 (2019) - [i18]Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin:
Self-Educated Language Agent With Hindsight Experience Replay For Instruction Following. CoRR abs/1910.09451 (2019) - 2018
- [c100]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, Joel Z. Leibo, Audrunas Gruslys:
Deep Q-learning From Demonstrations. AAAI 2018: 3223-3230 - [c99]Julien Pérolat, Bilal Piot, Olivier Pietquin:
Actor-Critic Fictitious Play in Simultaneous Move Multistage Games. AISTATS 2018: 919-928 - [c98]Merwan Barlier, Romain Laroche, Olivier Pietquin:
Training Dialogue Systems With Human Advice. AAMAS 2018: 999-1007 - [c97]Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin:
Visual Reasoning with Multi-hop Feature Modulation. ECCV (5) 2018: 808-831 - [c96]Alexandre Berard, Laurent Besacier, Ali Can Kocabiyikoglu, Olivier Pietquin:
End-to-End Automatic Speech Translation of Audiobooks. ICASSP 2018: 6224-6228 - [c95]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, Shane Legg:
Noisy Networks For Exploration. ICLR (Poster) 2018 - [p2]Gil Keren, Amr El-Desoky Mousa, Olivier Pietquin, Stefanos Zafeiriou, Björn W. Schuller:
Deep learning for multisensorial and multimodal interaction. The Handbook of Multimodal-Multisensor Interfaces, Volume 2 (2) 2018: 99-128 - [i17]Alexandre Bérard, Laurent Besacier, Ali Can Kocabiyikoglu, Olivier Pietquin:
End-to-End Automatic Speech Translation of Audiobooks. CoRR abs/1802.04200 (2018) - [i16]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, Olivier Pietquin:
Observe and Look Further: Achieving Consistent Performance on Atari. CoRR abs/1805.11593 (2018) - [i15]Florian Strub, Mathieu Seurin, Ethan Perez, Harm de Vries, Jérémie Mary, Philippe Preux, Aaron C. Courville, Olivier Pietquin:
Visual Reasoning with Multi-hop Feature Modulation. CoRR abs/1808.04446 (2018) - [i14]Julien Pérolat, Mateusz Malinowski, Bilal Piot, Olivier Pietquin:
Playing the Game of Universal Adversarial Perturbations. CoRR abs/1809.07802 (2018) - 2017
- [j14]Bilal Piot
, Matthieu Geist, Olivier Pietquin:
Bridging the Gap Between Imitation Learning and Inverse Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. 28(8): 1814-1826 (2017) - [c94]Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin:
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. AISTATS 2017: 232-241 - [c93]Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville:
GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. CVPR 2017: 4466-4475 - [c92]Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin:
End-to-end optimization of goal-driven and visually grounded dialogue systems. IJCAI 2017: 2765-2771 - [c91]Matthieu Geist, Bilal Piot, Olivier Pietquin:
Is the Bellman residual a bad proxy? NIPS 2017: 3205-3214 - [c90]Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville:
Modulating early visual processing by language. NIPS 2017: 6594-6604 - [c89]Alexandre Berard, Laurent Besacier, Olivier Pietquin:
LIG-CRIStAL Submission for the WMT 2017 Automatic Post-Editing Task. WMT 2017: 623-629 - [i13]Florian Strub, Harm de Vries, Jérémie Mary, Bilal Piot, Aaron C. Courville, Olivier Pietquin:
End-to-end optimization of goal-driven and visually grounded dialogue systems. CoRR abs/1703.05423 (2017) - [i12]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:
Learning from Demonstrations for Real World Reinforcement Learning. CoRR abs/1704.03732 (2017) - [i11]Diana Borsa, Bilal Piot, Rémi Munos, Olivier Pietquin:
Observational Learning by Reinforcement Learning. CoRR abs/1706.06617 (2017) - [i10]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:
Noisy Networks for Exploration. CoRR abs/1706.10295 (2017) - [i9]Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville:
Modulating early visual processing by language. CoRR abs/1707.00683 (2017) - [i8]Alexandre Berard, Olivier Pietquin, Laurent Besacier:
LIG-CRIStAL System for the WMT17 Automatic Post-Editing Task. CoRR abs/1707.05118 (2017) - [i7]Matej Vecerík, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, Martin A. Riedmiller:
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards. CoRR abs/1707.08817 (2017) - 2016
- [c88]Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin:
On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games. AISTATS 2016: 893-901 - [c87]Layla El Asri, Bilal Piot, Matthieu Geist, Romain Laroche, Olivier Pietquin:
Score-based Inverse Reinforcement Learning. AAMAS 2016: 457-465 - [c86]Hadrien Glaude, Olivier Pietquin:
PAC learning of Probabilistic Automaton based on the Method of Moments. ICML 2016: 820-829 - [c85]Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin:
Softened Approximate Policy Iteration for Markov Games. ICML 2016: 1860-1868 - [c84]Merwan Barlier, Romain Laroche, Olivier Pietquin:
A Stochastic Model for Computer-Aided Human-Human Dialogue. INTERSPEECH 2016: 2051-2055 - [c83]Layla El Asri, Romain Laroche, Olivier Pietquin:
Compact and Interpretable Dialogue State Representation with Genetic Sparse Distributed Memory. IWSDS 2016: 39-51 - [c82]Alexandre Berard, Christophe Servan, Olivier Pietquin, Laurent Besacier:
MultiVec: a Multilingual and Multilevel Representation Learning Toolkit for NLP. LREC 2016 - [c81]Merwan Barlier, Romain Laroche, Olivier Pietquin:
Learning dialogue dynamics with the method of moments. SLT 2016: 98-105 - [p1]Stéphane Dupont, Hüseyin Çakmak, William Curran, Thierry Dutoit, Jennifer Hofmann, Gary McKeown, Olivier Pietquin, Tracey Platt, Willibald Ruch, Jérôme Urbain:
Laughter Research: A Review of the ILHAIRE Project. Toward Robotic Socially Believable Behaving Systems (I) 2016: 147-181 - [i6]Bilal Piot, Matthieu Geist, Olivier Pietquin:
Difference of Convex Functions Programming Applied to Control with Expert Data. CoRR abs/1606.01128 (2016) - [i5]Matthieu Geist, Bilal Piot, Olivier Pietquin:
Should one minimize the expected Bellman residual or maximize the mean value? CoRR abs/1606.07636 (2016) - [i4]Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin:
Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. CoRR abs/1606.08718 (2016) - [i3]Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville:
GuessWhat?! Visual object discovery through multi-modal dialogue. CoRR abs/1611.08481 (2016) - [i2]Alexandre Berard, Olivier Pietquin, Christophe Servan, Laurent Besacier:
Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation. CoRR abs/1612.01744 (2016) - 2015
- [j13]Timothé Collet, Olivier Pietquin:
Optimism in Active Learning. Comput. Intell. Neurosci. 2015: 973696:1-973696:17 (2015) - [c80]Hadrien Glaude, Cyrille Enderli, Olivier Pietquin:
Spectral learning with non negative probabilities for finite state automaton. ASRU 2015: 71-77 - [c79]Bilal Piot, Olivier Pietquin, Matthieu Geist:
Imitation Learning Applied to Embodied Conversational Agents. MLIS@ICML 2015: 1-5 - [c78]Heriberto Cuayáhuitl, Nina Dethlefs, Lutz Frommberger, Martijn van Otterlo, Olivier Pietquin:
Proceedings of the 4th Workshop on Machine Learning for Interactive Systems (MLIS-2015). MLIS@ICML 2015: 4 - [c77]Julien Pérolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin:
Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games. ICML 2015: 1321-1329 - [c76]Hadrien Glaude, Cyrille Enderli, Olivier Pietquin:
Non-negative Spectral Learning for Linear Sequential Systems. ICONIP (2) 2015: 143-151 - [c75]Timothé Collet, Olivier Pietquin:
Optimism in Active Learning with Gaussian Processes. ICONIP (2) 2015: 152-160 - [c74]Thibaut Munzer, Bilal Piot, Matthieu Geist, Olivier Pietquin, Manuel Lopes:
Inverse Reinforcement Learning in Relational Domains. IJCAI 2015: 3735-3741 - [c73]Hadrien Glaude, Cyrille Enderli, Jean-François Grandin, Olivier Pietquin:
Learning of scanning strategies for electronic support using predictive state representations. MLSP 2015: 1-6 - [c72]Merwan Barlier, Julien Pérolat, Romain Laroche, Olivier Pietquin:
Human-Machine Dialogue as a Stochastic Game. SIGDIAL Conference 2015: 2-11 - [c71]Timothé Collet, Olivier Pietquin:
Bayesian Credible Intervals for Online and Active Learning of Classification Trees. SSCI 2015: 571-578 - 2014
- [c70]Timothé Collet, Olivier Pietquin:
Active learning for classification: An optimistic approach. ADPRL 2014: 1-8 - [c69]Hadrien Glaude, Olivier Pietquin, Cyrille Enderli:
Subspace identification for predictive state representation by nuclear norm minimization. ADPRL 2014: 1-8 - [c68]Bilal Piot, Matthieu Geist, Olivier Pietquin:
Boosted and reward-regularized classification for apprenticeship learning. AAMAS 2014: 1249-1256 - [c67]Layla El Asri, Hatim Khouzaimi, Romain Laroche, Olivier Pietquin:
Ordinal regression for interaction quality prediction. ICASSP 2014: 3221-3225 - [c66]Bilal Piot, Olivier Pietquin, Matthieu Geist:
Predicting when to laugh with structured classification. INTERSPEECH 2014: 1786-1790 - [c65]Layla El Asri, Rémi Lemonnier, Romain Laroche, Olivier Pietquin, Hatim Khouzaimi:
NASTIA: Negotiating Appointment Setting Interface. LREC 2014: 266-271 - [c64]Layla El Asri, Romain Laroche, Olivier Pietquin:
DINASTI: Dialogues with a Negotiating Appointment Setting Interface. LREC 2014: 272-278 - [c63]Bilal Piot, Matthieu Geist, Olivier Pietquin:
Difference of Convex Functions Programming for Reinforcement Learning. NIPS 2014: 2519-2527 - [c62]Bilal Piot, Matthieu Geist, Olivier Pietquin:
Boosted Bellman Residual Minimization Handling Expert Demonstrations. ECML/PKDD (2) 2014: 549-564 - [i1]Matthieu Geist, Olivier Pietquin:
Kalman Temporal Differences. CoRR abs/1406.3270 (2014) - 2013
- [j12]Olivier Pietquin, Helen F. Hastie:
A survey on metrics for the evaluation of user simulations. Knowl. Eng. Rev. 28(1): 59-73 (2013) - [j11]Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin:
Classification structurée pour l'apprentissage par renforcement inverse. Rev. d'Intelligence Artif. 27(2): 155-169 (2013) - [j10]Matthieu Geist, Olivier Pietquin:
Algorithmic Survey of Parametric Value Function Approximation. IEEE Trans. Neural Networks Learn. Syst. 24(6): 845-867 (2013) - [c61]Radoslaw Niewiadomski, Jennifer Hofmann, Jérôme Urbain, Tracey Platt, Johannes Wagner, Bilal Piot, Hüseyin Çakmak, Sathish Pammi, Tobias Baur, Stéphane Dupont, Matthieu Geist, Florian Lingenfelser, Gary McKeown, Olivier Pietquin, Willibald Ruch:
Laugh-aware virtual agent and its impact on user amusement. AAMAS 2013: 619-626 - [c60]Lucie Daubigney, Matthieu Geist, Olivier Pietquin:
Random projections: A remedy for overfitting issues in time series prediction with echo state networks. ICASSP 2013: 3253-3257 - [c59]Maurizio Mancini, Laurent Ach, Emeline Bantegnie, Tobias Baur, Nadia Berthouze, Debajyoti Datta, Yu Ding, Stéphane Dupont, Harry J. Griffin, Florian Lingenfelser, Radoslaw Niewiadomski, Catherine Pelachaud, Olivier Pietquin, Bilal Piot, Jérôme Urbain, Gualtiero Volpe, Johannes Wagner:
Laugh When You're Winning. eNTERFACE 2013: 50-79 - [c58]Olivier Pietquin:
Inverse reinforcement learning for interactive systems. MLIS@IJCAI 2013: 71-75 - [c57]Lucie Daubigney, Matthieu Geist, Olivier Pietquin:
Particle swarm optimisation of spoken dialogue system strategies. INTERSPEECH 2013: 470-474 - [c56]Edouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin:
A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning. ECML/PKDD (1) 2013: 1-16 - [c55]Bilal Piot, Matthieu Geist, Olivier Pietquin:
Learning from Demonstrations: Is It Worth Estimating a Reward Function? ECML/PKDD (1) 2013: 17-32 - [c54]Lucie Daubigney, Matthieu Geist, Olivier Pietquin:
Model-free POMDP optimisation of tutoring systems with echo-state networks. SIGDIAL Conference 2013: 102-106 - [c53]Layla El Asri, Romain Laroche, Olivier Pietquin:
Reward Shaping for Statistical Optimisation of Dialogue Management. SLSP 2013: 93-101 - 2012
- [j9]Jason D. Williams, Kai Yu, Brahim Chaib-draa, Oliver Lemon, Roberto Pieraccini, Olivier Pietquin, Pascal Poupart, Steve J. Young:
Introduction to the Issue on Advances in Spoken Dialogue Systems and Mobile Interface. IEEE J. Sel. Top. Signal Process. 6(8): 889-890 (2012) - [j8]Lucie Daubigney, Matthieu Geist, Senthilkumar Chandramohan, Olivier Pietquin:
A Comprehensive Reinforcement Learning Framework for Dialogue Management Optimization. IEEE J. Sel. Top. Signal Process. 6(8): 891-902 (2012) - [c52]Senthilkumar Chandramohan, Matthieu Geist, Fabrice Lefèvre, Olivier Pietquin:
Behavior Specific User Simulation in Spoken Dialogue Systems. ITG Conference on Speech Communication 2012: 1-4 - [c51]Olivier Pietquin, Fabio Tango:
A Reinforcement Learning Approach to Optimize the longitudinal Behavior of a Partial Autonomous Driving Assistance System. ECAI 2012: 987-992 - [c50]Senthilkumar Chandramohan, Matthieu Geist, Fabrice Lefèvre, Olivier Pietquin:
Clustering behaviors of Spoken Dialogue Systems users. ICASSP 2012: 4981-4984 - [c49]Lucie Daubigney, Matthieu Geist, Olivier Pietquin:
Off-policy learning in large-scale POMDP-based dialogue systems. ICASSP 2012: 4989-4992 - [c48]Senthilkumar Chandramohan, Matthieu Geist, Fabrice Lefèvre, Olivier Pietquin:
Co-adaptation in Spoken Dialogue Systems. IWSDS 2012: 343-353 - [c47]Olivier Pietquin:
Statistical User Simulation for Spoken Dialogue Systems: What for, Which Data, Which Future? SDCTD@NAACL-HLT 2012: 9-10 - [c46]Edouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin:
Inverse Reinforcement Learning through Structured Classification. NIPS 2012: 1016-1024 - [c45]Layla El Asri, Romain Laroche, Olivier Pietquin:
Reward Function Learning for Dialogue Management. STAIRS 2012: 95-106 - [c44]