About
Discord Stateoftheart AI
GitHub

Publications

27

Cited by

1349

Peter Henderson

machine learningreinforcement learningnatural language processing

Stanford University

Papers and Citations

1 - 50
Deep reinforcement learning that matters
2018
David Meger
Philip Bachman
Riashat Islam
+3
Cited by 898
An introduction to deep reinforcement learning
2018
Riashat Islam
Peter Henderson
Marc G. Bellemare
+2
Cited by 390
A survey of available corpora for building data-driven dialogue systems
2015
Peter Henderson
Iulian Vlad Serban
Laurent Charlin
+2
Cited by 257
A survey of available corpora for building data-driven dialogue systems: The journal version
2018
Peter Henderson
Iulian Vlad Serban
Ryan Lowe
+2
Cited by 207
Reproducibility of benchmarked deep reinforcement learning tasks for continuous control
2017
Peter Henderson
Maziar Gomrokchi
Doina Precup
+2
Cited by 156
Toward trustworthy AI development: mechanisms for supporting verifiable claims
2020
Elizabeth Seger
Rebecca Kagan
Markus Anderljung
+56
Cited by 54
Ethical challenges in data-driven dialogue systems
2018
Ryan Lowe
Genevieve Fried
Nan Rosemary Ke
+4
Cited by 49
Towards the systematic reporting of the energy and carbon footprints of machine learning
2020
Joelle Pineau
Jieru Hu
Dan Jurafsky
+4
Cited by 38
Benchmark environments for multitask learning in continuous domains
2017
Peter Henderson
Johanna Hansen
Wei-Di Chang
+3
Cited by 33
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning
2018
Joelle Pineau
David Meger
Pierre-Luc Bacon
+3
Cited by 33
Underwater multi-robot convoying using visual tracking by detection
2017
Wei-Di Chang
Junaed Sattar
Peter Henderson
+7
Cited by 24
Learning robust dialog policies in noisy environments
2017
Jin Cao
Jared Casale
Peter Henderson
+4
Cited by 20
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
2018
Peter Henderson
Joelle Pineau
Joshua Romoff
+2
Cited by 17
Where did my optimum go?: An empirical analysis of gradient descent optimization in policy gradient methods
2018
Joshua Romoff
Joelle Pineau
Peter Henderson
Cited by 14
Bayesian policy gradients via alpha divergence dropout inference
2017
Thang Doan
Riashat Islam
David Meger
+1
Cited by 12
With Little Power Comes Great Responsibility
2020
Urvashi Khandelwal
Peter Henderson
Dallas Card
+1
Cited by 11
Separating value functions across time-scales
2019
Y Ollivier
Joelle Pineau
Emma Brunskill
+3
Cited by 4
Implanted intracortical electrodes as chronic neural interfaces to the central nervous system
2015
Peter Henderson
Cited by 2
Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research
2018
Emma Brunskill
Peter Henderson
Cited by 2
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning
2021
Pierre-Luc Bacon
Dilip Arumugam
Peter Henderson
Cited by 1
Reproducibility and reusability in deep reinforcement learning
2018
Peter Henderson
Cited by 1
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
2020
Peter Henderson
Joshua Romoff
Joelle Pineau
+4
Cited by 1
An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models
2017
M Vertescher
Peter Henderson
Cited by 1
Chaotic Memory Randomization for Securing Embedded Systems
2016
Muthucumaru Maheswaran
Peter Henderson
Cited by 1
The RLLChatbot: a solution to the ConvAI challenge
2018
Michael Noseworthy
Prasanna Parthasarathi
Peter Henderson
+4
Cited by 1
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset
2021
Neel Guha
L Zheng
Peter Henderson
+1
Cited by
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?
2021
Emmanuel Bengio
Peter Henderson
David Kanaa
+1
Cited by
Adversarial Gain
2018
RN Ke
Peter Henderson
Koustuv Sinha
+1
Cited by
Cost Adaptation for Robust Decentralized Swarm Behaviour
2018
M Vertescher
M Coates
David Meger
+1
Cited by
Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop
2020
Carl Shneider
Joel Lehman
Lauren Baker
+5
Cited by