Peter Henderson
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Deep Reinforcement Learning that Matters
P Henderson*, R Islam*, P Bachman, J Pineau, D Precup, D Meger
AAAI Conference on Artificial Intelligence (AAAI), 2018
On the opportunities and risks of foundation models
R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ...
arXiv preprint arXiv:2108.07258, 2021
An Introduction to Deep Reinforcement Learning
V François-Lavet, P Henderson, R Islam, MG Bellemare, J Pineau
Foundations and Trends® in Machine Learning 11 (3-4), 219-354, 2018
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
arXiv preprint arXiv:2211.05100, 2022
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version
IV Serban, R Lowe, P Henderson, L Charlin, J Pineau
Dialogue & Discourse 9 (1), 1-49, 2018
Towards the systematic reporting of the energy and carbon footprints of machine learning
P Henderson, J Hu, J Romoff, E Brunskill, D Jurafsky, J Pineau
Journal of Machine Learning Research 21 (248), 1-43, 2020
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control
R Islam*, P Henderson*, M Gomrokchi, D Precup
Reproducibility in Machine Learning Workshop (ICML), 2017
Holistic Evaluation of Language Models
P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ...
arXiv preprint arXiv:2211.09110, 2022
Ethical Challenges in Data-Driven Dialogue Systems
P Henderson, K Sinha, N Angelard-Gontier, NR Ke, G Fried, R Lowe, ...
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2018
When does pretraining help? assessing self-supervised learning for law and the CaseHOLD dataset of 53,000+ legal holdings
L Zheng*, N Guha*, BR Anderson, P Henderson, DE Ho
Proceedings of the Eighteenth International Conference on Artificial …, 2021
With Little Power Comes Great Responsibility
D Card, P Henderson, U Khandelwal, R Jia, K Mahowald, D Jurafsky
arXiv preprint arXiv:2010.06595, 2020
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning
P Henderson, WD Chang, PL Bacon, D Meger, J Pineau, D Precup
AAAI Conference on Artificial Intelligence (AAAI), 2018
Underwater Multi-Robot Convoying using Visual Tracking by Detection
F Shkurti, WD Chang, P Henderson, MJ Islam, JCG Higuera, J Li, ...
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017
Benchmark Environments for Multitask Learning in Continuous Domains
P Henderson, WD Chang, F Shkurti, J Hansen, D Meger, G Dudek
Lifelong Learning: A Reinforcement Learning Approach Workshop (ICML), 2017
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
J Romoff*, P Henderson*, A Piche, V Francois-Lavet, J Pineau
2nd Conference on Robot Learning (CoRL), 2018
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods
P Henderson, J Romoff, J Pineau
The 14th European Workshop on Reinforcement Learning (EWRL 2018), 2018
Data Governance in the Age of Large-Scale Data-Driven Language Technology
Y Jerncite, H Nguyen, S Biderman, A Rogers, V Danchev, S Tan, ...
Learning Robust Dialog Policies in Noisy Environments
M Fazel-Zarandi, SW Li, J Cao, J Casale, P Henderson, D Whitney, ...
Conversational AI Workshop (NeurIPS), 2017
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
P Henderson*, MS Krass*, L Zheng, N Guha, CD Manning, D Jurafsky, ...
arXiv preprint arXiv:2207.00220, 2022
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