Peter Henderson
Cited by
Cited by
Deep Reinforcement Learning that Matters
P Henderson, R Islam, P Bachman, J Pineau, D Precup, D Meger
AAAI Conference on Artificial Intelligence (AAAI), 2018
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
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
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
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
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
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
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
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
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
With Little Power Comes Great Responsibility
D Card, P Henderson, U Khandelwal, R Jia, K Mahowald, D Jurafsky
arXiv preprint arXiv:2010.06595, 2020
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
J Romoff, A Piche, P Henderson, V Francois-Lavet, J Pineau
International Conference on Learning Representations Workshop (ICLR), 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
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
Bayesian Policy Gradients via Alpha Divergence Dropout Inference
P Henderson, T Doan, R Islam, D Meger
Bayesian Deep Learning Workshop (NeurIPS), 2017
Orıon: Asynchronous Distributed Hyperparameter Optimization
X Bouthillier, C Tsirigotis, F Corneau-Tremblay, P Delaunay, R Askari, ...
Zenodo, 2019
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset
L Zheng, N Guha, BR Anderson, P Henderson, DE Ho
arXiv preprint arXiv:2104.08671, 2021
Separating value functions across time-scales
J Romoff, P Henderson, A Touati, E Brunskill, J Pineau, Y Ollivier
International Conference on Machine Learning, 5468-5477, 2019
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?
J Romoff, P Henderson, D Kanaa, E Bengio, A Touati, PL Bacon, J Pineau
Proceedings of the 20th International Conference on Autonomous Agents and …, 2021
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