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ORCIDPeter Henderson 0002
Person information
- affiliation: Stanford University, CA, USA
- affiliation (former): McGill University, Montreal, QC, Canada
Other persons with the same name
- Peter Henderson 0001 — University of Southampton, School of Electronics and Computer Science, UK (and 1 more)
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2020 – today
- 2022
[c14]Peter Henderson, Ben Chugg, Brandon R. Anderson, Daniel E. Ho:
Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy. CSLAW 2022: 87-100- [c13]Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gérard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Dragomir R. Radev, Aaron Gokaslan, Somaieh Nikpoor, Peter Henderson, Rishi Bommasani, Margaret Mitchell:
Data Governance in the Age of Large-Scale Data-Driven Language Technology. FAccT 2022: 2206-2222 - [c12]Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab:
Text Characterization Toolkit (TCT). AACL/IJCNLP (System Demonstrations) 2022: 72-87 - [i35]Peter Henderson, Ben Chugg, Brandon R. Anderson, Kristen M. Altenburger, Alex Turk, John Guyton, Jacob Goldin, Daniel E. Ho:
Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection. CoRR abs/2204.11910 (2022) - [i34]Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Gérard Dupont, Jesse Dodge, Kyle Lo, Zeerak Talat, Isaac Johnson, Dragomir R. Radev, Somaieh Nikpoor, Jörg Frohberg, Aaron Gokaslan, Peter Henderson, Rishi Bommasani, Margaret Mitchell:
Data Governance in the Age of Large-Scale Data-Driven Language Technology. CoRR abs/2206.03216 (2022) - [i33]Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho:
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. CoRR abs/2207.00220 (2022) - [i32]Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho:
Entropy Regularization for Population Estimation. CoRR abs/2208.11747 (2022) - [i31]Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab:
Text Characterization Toolkit. CoRR abs/2210.01734 (2022) - [i30]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - [i29]Eric Mitchell, Peter Henderson, Christopher D. Manning, Dan Jurafsky, Chelsea Finn:
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models. CoRR abs/2211.14946 (2022) - 2021
- [c11]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 - [c10]Lucia Zheng, Neel Guha, Brandon R. Anderson
, Peter Henderson, Daniel E. Ho:
When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53, 000+ legal holdings. ICAIL 2021: 159-168 - [i28]Dilip Arumugam, Peter Henderson, Pierre-Luc Bacon:
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning. CoRR abs/2103.06224 (2021) - [i27]Lucia Zheng, Neel Guha, Brandon R. Anderson, Peter Henderson, Daniel E. Ho:
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset. CoRR abs/2104.08671 (2021) - [i26]Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.:
On the Opportunities and Risks of Foundation Models. CoRR abs/2108.07258 (2021) - [i25]Peter Henderson, Ben Chugg, Brandon R. Anderson, Daniel E. Ho:
Beyond Ads: Sequential Decision-Making Algorithms in Public Policy. CoRR abs/2112.06833 (2021) - 2020
- [c9]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. EMNLP (1) 2020: 9263-9274 - [i24]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) - [i23]Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung:
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR abs/2004.07213 (2020) - [i22]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) - [i21]Shagun Sodhani, Mayoore S. Jaiswal, Lauren Baker, Koustuv Sinha, Carl Shneider, Peter Henderson, Joel Lehman, Ryan Lowe:
Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop. CoRR abs/2007.10546 (2020) - [i20]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. CoRR abs/2010.06595 (2020)
2010 – 2019
- 2019
- [c8]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill:
Separable value functions across time-scales. ICML 2019: 5468-5477 - [i19]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau:
Separating value functions across time-scales. CoRR abs/1902.01883 (2019) - 2018
- [j2]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version. Dialogue Discourse 9(1): 1-49 (2018) - [j1]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. 11(3-4): 219-354 (2018) - [c7]Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup:
OptionGAN: Learning Joint Reward-Policy Options Using Generative Adversarial Inverse Reinforcement Learning. AAAI 2018: 3199-3206 - [c6]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning That Matters. AAAI 2018: 3207-3214 - [c5]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. AIES 2018: 123-129 - [c4]Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL 2018: 674-699 - [c3]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) 2018 - [c2]Peter Henderson, Matthew Vertescher, David Meger, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. IROS 2018: 4099-4106 - [i18]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR abs/1805.03359 (2018) - [i17]Peter Henderson, Joshua Romoff, Joelle Pineau:
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods. CoRR abs/1810.02525 (2018) - [i16]Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau:
Adversarial Gain. CoRR abs/1811.01302 (2018) - [i15]Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban, Michael D. Noseworthy, Prasanna Parthasarathi, Joelle Pineau:
The RLLChatbot: a solution to the ConvAI challenge. CoRR abs/1811.02714 (2018) - [i14]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. CoRR abs/1811.12560 (2018) - [i13]Peter Henderson, Emma Brunskill:
Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research. CoRR abs/1812.01074 (2018) - 2017
- [c1]Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar:
Underwater multi-robot convoying using visual tracking by detection. IROS 2017: 4189-4196 - [i12]Peter Henderson, Matthew Vertescher:
An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models. CoRR abs/1702.05156 (2017) - [i11]Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup:
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. CoRR abs/1708.04133 (2017) - [i10]Peter Henderson, Wei-Di Chang, Florian Shkurti, Johanna Hansen, David Meger, Gregory Dudek:
Benchmark Environments for Multitask Learning in Continuous Domains. CoRR abs/1708.04352 (2017) - [i9]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning that Matters. CoRR abs/1709.06560 (2017) - [i8]Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup:
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning. CoRR abs/1709.06683 (2017) - [i7]Peter Henderson, Matthew Vertescher, David Meger, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. CoRR abs/1709.07114 (2017) - [i6]Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar:
Underwater Multi-Robot Convoying using Visual Tracking by Detection. CoRR abs/1709.08292 (2017) - [i5]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. CoRR abs/1711.09050 (2017) - [i4]Peter Henderson, Thang Doan, Riashat Islam, David Meger:
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR abs/1712.02037 (2017) - [i3]Maryam Fazel-Zarandi, Shang-Wen Li, Jin Cao, Jared Casale, Peter Henderson, David Whitney, Alborz Geramifard:
Learning Robust Dialog Policies in Noisy Environments. CoRR abs/1712.04034 (2017) - 2016
- [i2]Peter Henderson, Muthucumaru Maheswaran:
Chaotic Memory Randomization for Securing Embedded Systems. CoRR abs/1611.00742 (2016) - 2015
- [i1]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora for Building Data-Driven Dialogue Systems. CoRR abs/1512.05742 (2015)
Coauthor Index
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