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ORCIDJoelle Pineau
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- affiliation: McGill University, Montreal, Canada
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2020 – today
- 2023
[j38]Martin Cousineau
, Vedat Verter, Susan A. Murphy, Joelle Pineau:
Estimating causal effects with optimization-based methods: A review and empirical comparison. Eur. J. Oper. Res. 304(2): 367-380 (2023)- [j37]Madhulika Srikumar, Rebecca Finlay, Grace Abuhamad, Carolyn Ashurst, Rosie Campbell, Emily Campbell-Ratcliffe, Hudson Hongo, Sara R. Jordan, Joseph Lindley, Aviv Ovadya, Joelle Pineau:
Publisher Correction: Advancing ethics review practices in AI research. Nat. Mac. Intell. 5(1): 94 (2023) - [j36]Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau:
Group Fairness in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j35]Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Varun Gupta, Iulian Vlad Serban, Joelle Pineau:
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems. Int. J. Artif. Intell. Educ. 32(2): 323-349 (2022) - [j34]Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau:
Low-Rank Representation of Reinforcement Learning Policies. J. Artif. Intell. Res. 75: 597-636 (2022) - [j33]Madhulika Srikumar, Rebecca Finlay, Grace Abuhamad, Carolyn Ashurst, Rosie Campbell, Emily Campbell-Ratcliffe, Hudson Hongo, Sara R. Jordan, Joseph Lindley, Aviv Ovadya, Joelle Pineau:
Advancing ethics review practices in AI research. Nat. Mac. Intell. 4(12): 1061-1064 (2022) - [c151]Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau:
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions. AAAI 2022: 6829-6837 - [c150]Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer:
Improving Passage Retrieval with Zero-Shot Question Generation. EMNLP 2022: 3781-3797 - [c149]Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, Adina Williams:
The Curious Case of Absolute Position Embeddings. EMNLP (Findings) 2022: 4449-4472 - [c148]Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky:
New Insights on Reducing Abrupt Representation Change in Online Continual Learning. ICLR 2022 - [c147]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. ICML 2022: 24414-24429 - [c146]Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang:
Block Contextual MDPs for Continual Learning. L4DC 2022: 608-623 - [i119]Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau:
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions. CoRR abs/2201.01836 (2022) - [i118]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. CoRR abs/2202.07013 (2022) - [i117]Thang Doan, Seyed-Iman Mirzadeh, Joelle Pineau, Mehrdad Farajtabar:
Efficient Continual Learning Ensembles in Neural Network Subspaces. CoRR abs/2202.09826 (2022) - [i116]Martin Cousineau, Vedat Verter, Susan A. Murphy, Joelle Pineau:
Estimating causal effects with optimization-based methods: A review and empirical comparison. CoRR abs/2203.00097 (2022) - [i115]Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer:
Improving Passage Retrieval with Zero-Shot Question Generation. CoRR abs/2204.07496 (2022) - [i114]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. CoRR abs/2206.10658 (2022) - [i113]Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, Adina Williams:
The Curious Case of Absolute Position Embeddings. CoRR abs/2210.12574 (2022) - 2021
- [j32]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. 22: 164:1-164:20 (2021) - [c145]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI 2021: 10674-10681 - [c144]Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, Adina Williams:
UnNatural Language Inference. ACL/IJCNLP (1) 2021: 7329-7346 - [c143]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning? AAMAS 2021: 1082-1090 - [c142]Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton:
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. EACL 2021: 2816-2822 - [c141]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. EMNLP (1) 2021: 2888-2913 - [c140]Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams:
Sometimes We Want Ungrammatical Translations. EMNLP (Findings) 2021: 3205-3227 - [c139]Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau:
Learning Robust State Abstractions for Hidden-Parameter Block MDPs. ICLR 2021 - [c138]Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau:
Regularized Inverse Reinforcement Learning. ICLR 2021 - [c137]Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim:
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. ICML 2021: 6120-6130 - [c136]Shagun Sodhani, Amy Zhang, Joelle Pineau:
Multi-Task Reinforcement Learning with Context-based Representations. ICML 2021: 9767-9779 - [c135]Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche:
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs. NeurIPS 2021: 2004-2017 - [c134]Prasanna Parthasarathi, Mohamed Abdelsalam, Sarath Chandar, Joelle Pineau:
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. SIGDIAL 2021: 469-476 - [c133]Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar:
Do Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task ? SIGDIAL 2021: 477-488 - [c132]Lucas Caccia, Joelle Pineau:
SPeCiaL: Self-supervised Pretraining for Continual Learning. CSSL 2021: 91-103 - [p1]Sylvie Delacroix, Joelle Pineau, Jessica Montgomery:
Democratising the Digital Revolution: The Role of Data Governance. Reflections on Artificial Intelligence for Humanity 2021: 40-52 - [i112]Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, Adina Williams:
Unnatural Language Inference. CoRR abs/2101.00010 (2021) - [i111]Anuroop Sriram, Matthew J. Muckley, Koustuv Sinha, Farah Shamout, Joelle Pineau, Krzysztof J. Geras, Lea Azour, Yindalon Aphinyanaphongs, Nafissa Yakubova, William Moore:
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. CoRR abs/2101.04909 (2021) - [i110]Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton:
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. CoRR abs/2102.03419 (2021) - [i109]Shagun Sodhani, Amy Zhang, Joelle Pineau:
Multi-Task Reinforcement Learning with Context-based Representations. CoRR abs/2102.06177 (2021) - [i108]Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau:
Domain Adversarial Reinforcement Learning. CoRR abs/2102.07097 (2021) - [i107]Manan Tomar, Amy Zhang, Roberto Calandra, Matthew E. Taylor, Joelle Pineau:
Model-Invariant State Abstractions for Model-Based Reinforcement Learning. CoRR abs/2102.09850 (2021) - [i106]Kalesha Bullard, Douwe Kiela, Joelle Pineau, Jakob N. Foerster:
Quasi-Equivalence Discovery for Zero-Shot Emergent Communication. CoRR abs/2103.08067 (2021) - [i105]Lucas Caccia, Rahaf Aljundi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky:
Reducing Representation Drift in Online Continual Learning. CoRR abs/2104.05025 (2021) - [i104]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. CoRR abs/2104.06644 (2021) - [i103]Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams:
Sometimes We Want Translationese. CoRR abs/2104.07623 (2021) - [i102]Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche:
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs. CoRR abs/2106.00099 (2021) - [i101]Emmanuel Bengio, Joelle Pineau, Doina Precup:
Correcting Momentum in Temporal Difference Learning. CoRR abs/2106.03955 (2021) - [i100]Lucas Caccia, Joelle Pineau:
SPeCiaL: Self-Supervised Pretraining for Continual Learning. CoRR abs/2106.09065 (2021) - [i99]Prasanna Parthasarathi, Mohamed Abdelsalam, Joelle Pineau, Sarath Chandar:
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. CoRR abs/2106.10619 (2021) - [i98]Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar:
Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ? CoRR abs/2106.10622 (2021) - [i97]Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim:
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. CoRR abs/2106.10783 (2021) - [i96]Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang:
Block Contextual MDPs for Continual Learning. CoRR abs/2110.06972 (2021) - 2020
- [j31]Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio:
The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach. J. Artif. Intell. Res. 69: 571-612 (2020) - [j30]Nathan Peiffer-Smadja, Redwan Maatoug, François-Xavier Lescure, Eric D'ortenzio, Joelle Pineau, Jean-Rémi King:
Machine Learning for COVID-19 needs global collaboration and data-sharing. Nat. Mach. Intell. 2(6): 293-294 (2020) - [c131]Eric Crawford, Joelle Pineau:
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking. AAAI 2020: 3684-3692 - [c130]Qizhen Zhang, Audrey Durand, Joelle Pineau:
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract). AAAI 2020: 13983-13984 - [c129]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. ACL 2020: 2430-2441 - [c128]Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Varun Gupta, Iulian Vlad Serban, Joelle Pineau:
Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System. AIED (2) 2020: 140-146 - [c127]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED (2) 2020: 387-392 - [c126]Joelle Pineau:
Building reproducible, reusable, and robust machine learning software. DEBS 2020: 2 - [c125]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. ICLR 2020 - [c124]Ryan Lowe, Abhinav Gupta, Jakob N. Foerster, Douwe Kiela, Joelle Pineau:
On the interaction between supervision and self-play in emergent communication. ICLR 2020 - [c123]Emmanuel Bengio, Joelle Pineau, Doina Precup:
Interference and Generalization in Temporal Difference Learning. ICML 2020: 767-777 - [c122]Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau:
Online Learned Continual Compression with Adaptive Quantization Modules. ICML 2020: 1240-1250 - [c121]Harsh Satija, Philip Amortila, Joelle Pineau:
Constrained Markov Decision Processes via Backward Value Functions. ICML 2020: 8502-8511 - [c120]Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup:
Invariant Causal Prediction for Block MDPs. ICML 2020: 11214-11224 - [c119]Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau:
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI 2020: 2140-2147 - [c118]Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau:
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). IJCAI 2020: 5055-5059 - [c117]Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra:
Plan2Vec: Unsupervised Representation Learning by Latent Plans. L4DC 2020: 935-946 - [c116]Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai:
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization. NeurIPS 2020 - [c115]Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau:
Novelty Search in Representational Space for Sample Efficient Exploration. NeurIPS 2020 - [c114]Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent:
Stable Policy Optimization via Off-Policy Divergence Regularization. UAI 2020: 1328-1337 - [i95]Ryan Lowe, Abhinav Gupta, Jakob N. Foerster, Douwe Kiela, Joelle Pineau:
On the interaction between supervision and self-play in emergent communication. CoRR abs/2002.01093 (2020) - [i94]Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau:
Provably efficient reconstruction of policy networks. CoRR abs/2002.02863 (2020) - [i93]Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau:
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR abs/2002.05651 (2020) - [i92]Wonseok Jeon, Paul Barde, Derek Nowrouzezahrai, Joelle Pineau:
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic. CoRR abs/2002.10525 (2020) - [i91]Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent:
Stable Policy Optimization via Off-Policy Divergence Regularization. CoRR abs/2003.04108 (2020) - [i90]Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup:
Invariant Causal Prediction for Block MDPs. CoRR abs/2003.06016 (2020) - [i89]Emmanuel Bengio, Joelle Pineau, Doina Precup:
Interference and Generalization in Temporal Difference Learning. CoRR abs/2003.06350 (2020) - [i88]Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton:
Evaluating Logical Generalization in Graph Neural Networks. CoRR abs/2003.06560 (2020) - [i87]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR abs/2003.12206 (2020) - [i86]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. CoRR abs/2005.00583 (2020) - [i85]Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Varun Gupta, Iulian Vlad Serban, Joelle Pineau:
Automated Personalized Feedback Improves Learning Gains in an Intelligent Tutoring System. CoRR abs/2005.02431 (2020) - [i84]Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra:
Plan2Vec: Unsupervised Representation Learning by Latent Plans. CoRR abs/2005.03648 (2020) - [i83]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. CoRR abs/2005.06616 (2020) - [i82]Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Christopher J. Pal, Derek Nowrouzezahrai:
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization. CoRR abs/2006.13258 (2020) - [i81]Deepak Sharma, Audrey Durand, Marc-André Legault, Louis-Philippe Lemieux Perreault, Audrey Lemaçon, Marie-Pierre Dubé, Joelle Pineau:
Deep interpretability for GWAS. CoRR abs/2007.01516 (2020) - [i80]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? CoRR abs/2007.02786 (2020) - [i79]Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau:
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP. CoRR abs/2007.07206 (2020) - [i78]Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar:
How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics. CoRR abs/2008.10427 (2020) - [i77]Harsh Satija, Philip Amortila, Joelle Pineau:
Constrained Markov Decision Processes via Backward Value Functions. CoRR abs/2008.11811 (2020) - [i76]Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau:
Novelty Search in representational space for sample efficient exploration. CoRR abs/2009.13579 (2020) - [i75]Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau:
Regularized Inverse Reinforcement Learning. CoRR abs/2010.03691 (2020) - [i74]Kalesha Bullard, Franziska Meier, Douwe Kiela, Joelle Pineau, Jakob N. Foerster:
Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations. CoRR abs/2010.15896 (2020) - [i73]Melissa Mozifian, Amy Zhang, Joelle Pineau, David Meger:
Intervention Design for Effective Sim2Real Transfer. CoRR abs/2012.02055 (2020)
2010 – 2019
- 2019
- [j29]Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau:
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. J. Artif. Intell. Res. 65: 1-30 (2019) - [c113]Eric Crawford, Joelle Pineau:
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks. AAAI 2019: 3412-3420 - [c112]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
On-Line Adaptative Curriculum Learning for GANs. AAAI 2019: 3470-3477 - [c111]Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau:
Combined Reinforcement Learning via Abstract Representations. AAAI 2019: 3582-3589 - [c110]Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau:
Multitask Metric Learning: Theory and Algorithm. AISTATS 2019: 3362-3371 - [c109]Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin:
On the Pitfalls of Measuring Emergent Communication. AAMAS 2019: 693-701 - [c108]Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL 2019: 430-444 - [c107]Abhinav Gupta, Ryan Lowe, Jakob N. Foerster, Douwe Kiela, Joelle Pineau:
Seeded self-play for language learning. LANTERN@EMNLP-IJCNLP 2019: 62-66 - [c106]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. EMNLP/IJCNLP (1) 2019: 4505-4514 - [c105]Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, Joelle Pineau:
TarMAC: Targeted Multi-Agent Communication. ICML 2019: 1538-1546 - [c104]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill:
Separable value functions across time-scales. ICML 2019: 5468-5477 - [c103]Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau:
Deep Generative Modeling of LiDAR Data. IROS 2019: 5034-5040 - [c102]Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville:
No-Press Diplomacy: Modeling Multi-Agent Gameplay. NeurIPS 2019: 4476-4487 - [c101]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. NeurIPS 2019: 13299-13309 - [c100]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. UAI 2019: 422-432 - [i72]Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander H. Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, Shrimai Prabhumoye, Alan W. Black, Alexander I. Rudnicky, Jason D. Williams, Joelle Pineau, Mikhail Burtsev, Jason Weston:
The Second Conversational Intelligence Challenge (ConvAI2). CoRR abs/1902.00098 (2019) - [i71]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau:
Separating value functions across time-scales. CoRR abs/1902.01883 (2019) - [i70]Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin:
On the Pitfalls of Measuring Emergent Communication. CoRR abs/1903.05168 (2019) - [i69]Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR abs/1905.06893 (2019) - [i68]Pierre Thodoroff, Nishanth Anand, Lucas Caccia, Doina Precup, Joelle Pineau:
Recurrent Value Functions. CoRR abs/1905.09562 (2019) - [i67]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. CoRR