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With Little Power Comes Great Responsibility

Oct 13, 2020
Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky

* To appear at EMNLP 2020 

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Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop

Jul 21, 2020
Shagun Sodhani, Mayoore S. Jaiswal, Lauren Baker, Koustuv Sinha, Carl Shneider, Peter Henderson, Joel Lehman, Ryan Lowe


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TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?

Jul 06, 2020
Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau

* Presented at the Theoretical Foundations of Reinforcement Learning workshop at ICML 2020 

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Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning

Jan 31, 2020
Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau


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Separating value functions across time-scales

Feb 08, 2019
Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau


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Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research

Dec 03, 2018
Peter Henderson, Emma Brunskill

* Accepted to the Critiquing and Correcting Trends in Machine Learning Workshop (CRACT) at NeurIPS 2018 

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An Introduction to Deep Reinforcement Learning

Dec 03, 2018
Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau

* Foundations and Trends in Machine Learning: Vol. 11, No. 3-4, 2018 

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The RLLChatbot: a solution to the ConvAI challenge

Nov 08, 2018
Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban, Michael Noseworthy, Prasanna Parthasarathi, Joelle Pineau

* 46 pages including references and appendix, 14 figures, 12 tables; Under review for the Dialogue & Discourse journal 

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Adversarial Gain

Nov 04, 2018
Peter Henderson, Koustuv Sinha, Rosemary Nan Ke, Joelle Pineau


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Cost Adaptation for Robust Decentralized Swarm Behaviour

Sep 30, 2018
Peter Henderson, Matthew Vertescher, David Meger, Mark Coates

* Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018 

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Reward Estimation for Variance Reduction in Deep Reinforcement Learning

May 09, 2018
Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent Francois-Lavet, Joelle Pineau

* Accepted to the International Conference on Learning Representations (ICLR) 2018 Workshop Track 

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Learning Robust Dialog Policies in Noisy Environments

Dec 11, 2017
Maryam Fazel-Zarandi, Shang-Wen Li, Jin Cao, Jared Casale, Peter Henderson, David Whitney, Alborz Geramifard

* 1st Workshop on Conversational AI at NIPS 2017 

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Bayesian Policy Gradients via Alpha Divergence Dropout Inference

Dec 06, 2017
Peter Henderson, Thang Doan, Riashat Islam, David Meger

* Accepted to Bayesian Deep Learning Workshop at NIPS 2017 

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Deep Reinforcement Learning that Matters

Nov 24, 2017
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger

* Accepted to the Thirthy-Second AAAI Conference On Artificial Intelligence (AAAI), 2018 

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OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning

Nov 24, 2017
Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup

* Accepted to the Thirthy-Second AAAI Conference On Artificial Intelligence (AAAI), 2018 

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Ethical Challenges in Data-Driven Dialogue Systems

Nov 24, 2017
Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau

* In Submission to the AAAI/ACM conference on Artificial Intelligence, Ethics, and Society 

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Underwater Multi-Robot Convoying using Visual Tracking by Detection

Sep 25, 2017
Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar

* Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 

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Benchmark Environments for Multitask Learning in Continuous Domains

Aug 14, 2017
Peter Henderson, Wei-Di Chang, Florian Shkurti, Johanna Hansen, David Meger, Gregory Dudek

* Accepted at Lifelong Learning: A Reinforcement Learning Approach Workshop @ ICML, Sydney, Australia, 2017 

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Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Aug 10, 2017
Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup

* Accepted to Reproducibility in Machine Learning Workshop, ICML'17 

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A Survey of Available Corpora for Building Data-Driven Dialogue Systems

Mar 21, 2017
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau

* 56 pages including references and appendix, 5 tables and 1 figure; Under review for the Dialogue & Discourse journal. Update: paper has been rewritten and now includes several new datasets 

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An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models

Feb 16, 2017
Peter Henderson, Matthew Vertescher


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