Pineau, Joelle

104 publications

ICLR 2024 Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning Maxime Wabartha, Joelle Pineau

ICML 2024 Position: On the Societal Impact of Open Foundation Models Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan

TMLR 2023 Group Fairness in Reinforcement Learning Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau

NeurIPSW 2023 Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning Maxime Wabartha, Joelle Pineau

AAAI 2022 A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau

L4DC 2022 Block Contextual MDPs for Continual Learning Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang

JAIR 2022 Low-Rank Representation of Reinforcement Learning Policies Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau

ICLR 2022 New Insights on Reducing Abrupt Representation Change in Online Continual Learning Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky

ICML 2022 Robust Policy Learning over Multiple Uncertainty Sets Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang

NeurIPSW 2021 Block Contextual MDPs for Continual Learning Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang

JMLR 2021 Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program) Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Lariviere, Alina Beygelzimer, Florence d'Alche-Buc, Emily Fox, Hugo Larochelle

AAAI 2021 Improving Sample Efficiency in Model-Free Reinforcement Learning from Images Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus

ICLR 2021 Learning Robust State Abstractions for Hidden-Parameter Block MDPs Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau

NeurIPS 2021 Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche

ICML 2021 Multi-Task Reinforcement Learning with Context-Based Representations Shagun Sodhani, Amy Zhang, Joelle Pineau

ICML 2021 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation Jongmin Lee, Wonseok Jeon, Byungjun Lee, Joelle Pineau, Kee-Eung Kim

ICLR 2021 Regularized Inverse Reinforcement Learning Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau

NeurIPS 2020 Adversarial Soft Advantage Fitting: Imitation Learning Without Policy Optimization Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai

ICML 2020 Constrained Markov Decision Processes via Backward Value Functions Harsh Satija, Philip Amortila, Joelle Pineau

ICMLW 2020 Evaluating Logical Generalization in Graph Neural Networks Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton

AAAI 2020 Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking Eric Crawford, Joelle Pineau

IJCAI 2020 Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau

ICML 2020 Interference and Generalization in Temporal Difference Learning Emmanuel Bengio, Joelle Pineau, Doina Precup

ICML 2020 Invariant Causal Prediction for Block MDPs Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup

ICLR 2020 Language GANs Falling Short Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin

AAAI 2020 Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract) Qizhen Zhang, Audrey Durand, Joelle Pineau

NeurIPS 2020 Novelty Search in Representational Space for Sample Efficient Exploration Ruo Yu Tao, Vincent Francois-Lavet, Joelle Pineau

IJCAI 2020 On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract) Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau

ICLR 2020 On the Interaction Between Supervision and Self-Play in Emergent Communication Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau

ICML 2020 Online Learned Continual Compression with Adaptive Quantization Modules Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau

L4DC 2020 Plan2Vec: Unsupervised Representation Learning by Latent Plans Ge Yang, Amy Zhang, Ari Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra

UAI 2020 Stable Policy Optimization via Off-Policy Divergence Regularization Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent

JAIR 2020 The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio

JMLR 2020 Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau

AAAI 2019 Combined Reinforcement Learning via Abstract Representations Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau

NeurIPS 2019 Gossip-Based Actor-Learner Architectures for Deep Reinforcement Learning Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Michael Rabbat

ICMLW 2019 Learning to Learn to Communicate Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau

CoRL 2019 Leveraging Exploration in Off-Policy Algorithms via Normalizing Flows Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R Devon Hjelm

AISTATS 2019 Multitask Metric Learning: Theory and Algorithm Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau

NeurIPS 2019 No-Press Diplomacy: Modeling Multi-Agent Gameplay Philip Paquette, Yuchen Lu, Seton Steven Bocco, Max Smith, Satya O.-G., Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville

JAIR 2019 On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau

AAAI 2019 On-Line Adaptative Curriculum Learning for GANs Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm

UAI 2019 Randomized Value Functions via Multiplicative Normalizing Flows Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent

ICML 2019 Separating Value Functions Across Time-Scales Joshua Romoff, Peter Henderson, Ahmed Touati, Emma Brunskill, Joelle Pineau, Yann Ollivier

AAAI 2019 Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks Eric Crawford, Joelle Pineau

ICML 2019 TarMAC: Targeted Multi-Agent Communication Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, Joelle Pineau

ICML 2018 An Inference-Based Policy Gradient Method for Learning Options Matthew Smith, Herke Hoof, Joelle Pineau

FnTML 2018 An Introduction to Deep Reinforcement Learning Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau

MLHC 2018 Contextual Bandits for Adapting Treatment in a Mouse Model of De Novo Carcinogenesis Audrey Durand, Charis Achilleos, Demetris Iacovides, Katerina Strati, Georgios D. Mitsis, Joelle Pineau

AAAI 2018 Deep Reinforcement Learning That Matters Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger

ICML 2018 Focused Hierarchical RNNs for Conditional Sequence Processing Nan Rosemary Ke, Konrad Żołna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher Pal

AAAI 2018 OptionGAN: Learning Joint Reward-Policy Options Using Generative Adversarial Inverse Reinforcement Learning Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup

CoRL 2018 Reward Estimation for Variance Reduction in Deep Reinforcement Learning Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau

JMLR 2018 Streaming Kernel Regression with Provably Adaptive Mean, Variance, and Regularization Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau

NeurIPS 2018 Temporal Regularization for Markov Decision Process Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup

AAAI 2017 A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio

ICLR 2017 An Actor-Critic Algorithm for Sequence Prediction Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio

NeurIPS 2017 Multitask Spectral Learning of Weighted Automata Guillaume Rabusseau, Borja Balle, Joelle Pineau

ICLR 2017 Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses Ryan Lowe, Michael Noseworthy, Iulian Vlad Serban, Nicolas Angelard-Gontier, Yoshua Bengio, Joelle Pineau

AAAI 2016 Building End-to-End Dialogue Systems Using Generative Hierarchical Neural Network Models Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, Joelle Pineau

IJCAI 2016 Generalized Dictionary for Multitask Learning with Boosting Boyu Wang, Joelle Pineau

AAAI 2016 Incremental Stochastic Factorization for Online Reinforcement Learning André da Motta Salles Barreto, Rafael L. Beirigo, Joelle Pineau, Doina Precup

MLHC 2016 Learning Robust Features Using Deep Learning for Automatic Seizure Detection Pierre Thodoroff, Joelle Pineau, Andrew Lim

AAAI 2016 Multitask Generalized Eigenvalue Program Boyu Wang, Joelle Pineau, Borja Balle

JMLR 2016 Practical Kernel-Based Reinforcement Learning André M.S. Barreto, Doina Precup, Joelle Pineau

IJCAI 2015 An Expectation-Maximization Algorithm to Compute a Stochastic Factorization from Data André da Motta Salles Barreto, Rafael L. Beirigo, Joelle Pineau, Doina Precup

FnTML 2015 Bayesian Reinforcement Learning: A Survey Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar

AAAI 2015 Information Gathering and Reward Exploitation of Subgoals for POMDPs Hang Ma, Joelle Pineau

AAAI 2015 Online Boosting Algorithms for Anytime Transfer and Multitask Learning Boyu Wang, Joelle Pineau

JMLR 2014 Efficient Learning and Planning with Compressed Predictive States William Hamilton, Mahdi Milani Fard, Joelle Pineau

ICLR 2014 End-to-End Text Recognition with Hybrid HMM Maxout Models Ouais Alsharif, Joelle Pineau

ICML 2014 Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison Borja Balle, William Hamilton, Joelle Pineau

JAIR 2014 Policy Iteration Based on Stochastic Factorization André da Motta Salles Barreto, Joelle Pineau, Doina Precup

NeurIPS 2013 Bellman Error Based Feature Generation Using Random Projections on Sparse Spaces Mahdi Milani Fard, Yuri Grinberg, Amir-massoud Farahmand, Joelle Pineau, Doina Precup

NeurIPS 2013 Learning from Limited Demonstrations Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau, Doina Precup

AAAI 2013 Mixed Observability Predictive State Representations Sylvie C. W. Ong, Yuri Grinberg, Joelle Pineau

ICML 2013 Modelling Sparse Dynamical Systems with Compressed Predictive State Representations William L. Hamilton, Mahdi Milani Fard, Joelle Pineau

AAAI 2012 Compressed Least-Squares Regression on Sparse Spaces Mahdi Milani Fard, Yuri Grinberg, Joelle Pineau, Doina Precup

NeurIPS 2012 On-Line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization Andre Barreto, Doina Precup, Joelle Pineau

JMLR 2011 A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes Stéphane Ross, Joelle Pineau, Brahim Chaib-draa, Pierre Kreitmann

UAI 2011 Active Learning for Developing Personalized Treatment Kun Deng, Joelle Pineau, Susan A. Murphy

MLJ 2011 Informing Sequential Clinical Decision-Making Through Reinforcement Learning: An Empirical Study Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte, T. Scott Stroup, Joelle Pineau, Susan A. Murphy

JAIR 2011 Non-Deterministic Policies in Markovian Decision Processes Mahdi Milani Fard, Joelle Pineau

UAI 2011 PAC-Bayesian Policy Evaluation for Reinforcement Learning Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári

NeurIPS 2011 Reinforcement Learning Using Kernel-Based Stochastic Factorization Andre Barreto, Doina Precup, Joelle Pineau

NeurIPS 2010 PAC-Bayesian Model Selection for Reinforcement Learning Mahdi M. Fard, Joelle Pineau

NeurIPS 2009 Manifold Embeddings for Model-Based Reinforcement Learning Under Partial Observability Keith Bush, Joelle Pineau

IJCAI 2009 Wikispeedia: An Online Game for Inferring Semantic Distances Between Concepts Robert West, Joelle Pineau, Doina Precup

AAAI 2008 A Variance Analysis for POMDP Policy Evaluation Mahdi Milani Fard, Joelle Pineau, Peng Sun

AAAI 2008 Adaptive Treatment of Epilepsy via Batch-Mode Reinforcement Learning Arthur Guez, Robert D. Vincent, Massimo Avoli, Joelle Pineau

NeurIPS 2008 MDPs with Non-Deterministic Policies Mahdi M. Fard, Joelle Pineau

UAI 2008 Model-Based Bayesian Reinforcement Learning in Large Structured Domains Stéphane Ross, Joelle Pineau

JAIR 2008 Online Planning Algorithms for POMDPs Stéphane Ross, Joelle Pineau, Sébastien Paquet, Brahim Chaib-draa

ICML 2008 Reinforcement Learning with Limited Reinforcement: Using Bayes Risk for Active Learning in POMDPs Finale Doshi, Joelle Pineau, Nicholas Roy

NeurIPS 2007 Bayes-Adaptive POMDPs Stephane Ross, Brahim Chaib-draa, Joelle Pineau

NeurIPS 2007 Theoretical Analysis of Heuristic Search Methods for Online POMDPs Stephane Ross, Joelle Pineau, Brahim Chaib-draa

JAIR 2006 Anytime Point-Based Approximations for Large POMDPs Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun

ECML-PKDD 2006 PAC-Learning of Markov Models with Hidden State Ricard Gavaldà, Philipp W. Keller, Joelle Pineau, Doina Precup

AAAI 2006 Representing Systems with Hidden State Christopher Hundt, Prakash Panangaden, Joelle Pineau, Doina Precup

ECML-PKDD 2005 Active Learning in Partially Observable Markov Decision Processes Robin Jaulmes, Joelle Pineau, Doina Precup

NeurIPS 2003 Applying Metric-Trees to Belief-Point POMDPs Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun

IJCAI 2003 Point-Based Value Iteration: An Anytime Algorithm for POMDPs Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun

UAI 2003 Policy-Contingent Abstraction for Robust Robot Control Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun

AAAI 2002 Experiences with a Mobile Robotic Guide for the Elderly Michael Montemerlo, Joelle Pineau, Nicholas Roy, Sebastian Thrun, Vandi Verma