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Peter Henderson 0002
Person information
- affiliation: Princeton University, Center For Information Technology Policy, NJ, USA
- affiliation (former, PhD 2023): 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
- 2024
- [c26]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Aligned Large Language Models. AAAI 2024: 21527-21536 - [c25]Peter Henderson
, Jieru Hu
Rethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct. CSLAW 2024: 109-120 - [c24]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! ICLR 2024 - [c23]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
Position: On the Societal Impact of Open Foundation Models. ICML 2024 - [c22]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 2024 - [c21]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. ICML 2024 - [i54]Sayash Kapoor, Peter Henderson, Arvind Narayanan:
Promises and pitfalls of artificial intelligence for legal applications. CoRR abs/2402.01656 (2024) - [i53]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. CoRR abs/2402.05162 (2024) - [i52]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i51]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
On the Societal Impact of Open Foundation Models. CoRR abs/2403.07918 (2024) - [i50]Luxi He, Mengzhou Xia, Peter Henderson:
What's in Your "Safe" Data?: Identifying Benign Data that Breaks Safety. CoRR abs/2404.01099 (2024) - [i49]Joel Niklaus, Lucia Zheng, Arya D. McCarthy, Christopher Hahn, Brian M. Rosen, Peter Henderson, Daniel E. Ho, Garrett Honke, Percy Liang, Christopher D. Manning:
FLawN-T5: An Empirical Examination of Effective Instruction-Tuning Data Mixtures for Legal Reasoning. CoRR abs/2404.02127 (2024) - [i48]Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal:
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - [i47]Minzhou Pan, Yi Zeng, Xue Lin, Ning Yu, Cho-Jui Hsieh, Peter Henderson, Ruoxi Jia:
JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model Edits. CoRR abs/2406.03720 (2024) - [i46]Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson:
Safety Alignment Should Be Made More Than Just a Few Tokens Deep. CoRR abs/2406.05946 (2024) - [i45]Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson:
Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR abs/2406.14526 (2024) - [i44]Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal:
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors. CoRR abs/2406.14598 (2024) - [i43]Shayne Longpre, Stella Biderman, Alon Albalak, Hailey Schoelkopf, Daniel McDuff, Sayash Kapoor, Kevin Klyman, Kyle Lo, Gabriel Ilharco, Nay San, Maribeth Rauh, Aviya Skowron, Bertie Vidgen, Laura Weidinger, Arvind Narayanan, Victor Sanh, David Ifeoluwa Adelani, Percy Liang, Rishi Bommasani, Peter Henderson, Sasha Luccioni, Yacine Jernite, Luca Soldaini:
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources. CoRR abs/2406.16746 (2024) - [i42]Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. CoRR abs/2406.18664 (2024) - 2023
- [j4]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. J. Mach. Learn. Res. 24: 400:1-400:79 (2023) - [j3]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. Trans. Mach. Learn. Res. 2023 (2023) - [c20]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. AAAI 2023: 5087-5095 - [c19]Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho:
Entropy Regularization for Population Estimation. AAAI 2023: 12198-12204 - [c18]Peter Henderson
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. AIES 2023: 287-296 - [c17]Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, K. Aditya, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shang Gao, Spencer Williams, Sunny Gandhi, Tom Zur, Varun Iyer, Zehua Li:
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. NeurIPS 2023 - [c16]Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models. NeurIPS 2023 - [i41]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. CoRR abs/2303.15715 (2023) - [i40]Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs. CoRR abs/2305.02440 (2023) - [i39]Peter Henderson, Tatsunori Hashimoto, Mark A. Lemley:
Where's the Liability in Harmful AI Speech? CoRR abs/2308.04635 (2023) - [i38]Eugene Volokh, Mark A. Lemley, Peter Henderson:
Freedom of Speech and AI Output. CoRR abs/2308.08673 (2023) - [i37]Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shang Gao, Spencer Williams, Sunny Gandhi, Tom Zur, Varun Iyer, Zehua Li:
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models. CoRR abs/2308.11462 (2023) - [i36]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! CoRR abs/2310.03693 (2023) - 2022
- [c15]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 - [c14]Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers
Data Governance in the Age of Large-Scale Data-Driven Language Technology. FAccT 2022: 2206-2222 - [c13]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 - [c12]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. NeurIPS 2022 - [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
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
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
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 E. 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
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
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
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
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 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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