Peter Henderson

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 78

Top Topics

Temporal Difference

Reinforcement Learning

Dialogue System

Top Venues

Publications

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 (2024)
Luxi He, Mengzhou Xia, Peter Henderson
What's in Your "Safe" Data?: Identifying Benign Data that Breaks Safety. CoRR (2024)
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 (2024)
Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen 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 (2024)
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 (2024)
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 (2024)
Peter Henderson, Jieru Hu, Mona T. Diab, Joelle Pineau
Rethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct. CSLAW (2024)
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 (2024)
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)
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 (2024)
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 (2024)
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 (2024)
Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal
Visual Adversarial Examples Jailbreak Aligned Large Language Models. AAAI (2024)
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 (2024)
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. CoRR (2024)
Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models. NeurIPS (2023)
Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang
Foundation Models and Fair Use. CoRR (2023)
Eugene Volokh, Mark A. Lemley, Peter Henderson
Freedom of Speech and AI Output. CoRR (2023)
Peter Henderson, Eric Mitchell, Christopher D. Manning, Dan Jurafsky, Chelsea Finn
Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models. AIES (2023)
Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho
Entropy Regularization for Population Estimation. AAAI (2023)
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 (2023)
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)
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)
Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya K, 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)
Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs. CoRR (2023)
Peter Henderson, Tatsunori Hashimoto, Mark A. Lemley
Where's the Liability in Harmful AI Speech? CoRR (2023)
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 (2023)
Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab
Text Characterization Toolkit. CoRR (2022)
Ben Chugg, Peter Henderson, Jacob Goldin, Daniel E. Ho
Entropy Regularization for Population Estimation. CoRR (2022)
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)
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 (2022)
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 (2022)
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 (2022)
Peter Henderson, Ben Chugg, Brandon R. Anderson, Daniel E. Ho
Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy. CSLAW (2022)
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 (2022)
Yacine Jernite, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, Alexandra Sasha Luccioni, Nishant Subramani, Isaac Johnson, Gerard 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)
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 (2022)
Daniel Simig, Tianlu Wang, Verna Dankers, Peter Henderson, Khuyagbaatar Batsuren, Dieuwke Hupkes, Mona T. Diab
Text Characterization Toolkit (TCT). AACL/IJCNLP (System Demonstrations) (2022)
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ 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 (2021)
Dilip Arumugam, Peter Henderson, Pierre-Luc Bacon
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning. CoRR (2021)
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)
Peter Henderson, Ben Chugg, Brandon R. Anderson, Daniel E. Ho
Beyond Ads: Sequential Decision-Making Algorithms in Public Policy. CoRR (2021)
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)
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 (2021)
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 (2020)
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 (2020)
Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky
With Little Power Comes Great Responsibility. CoRR (2020)
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 (2020)
Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky
With Little Power Comes Great Responsibility. EMNLP (1) (2020)
Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? CoRR (2020)
Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau
Separating value functions across time-scales. CoRR (2019)
Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill
Separable value functions across time-scales. ICML (2019)
Peter Henderson, Matthew Vertescher, David Meger, Mark Coates
Cost Adaptation for Robust Decentralized Swarm Behaviour. IROS (2018)
Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban, Michael Noseworthy, Prasanna Parthasarathi, Joelle Pineau
The RLLChatbot: a solution to the ConvAI challenge. CoRR (2018)
Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau
Adversarial Gain. CoRR (2018)
Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR (2018)
Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL (2018)
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)
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger
Deep Reinforcement Learning That Matters. AAAI (2018)
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) (2018)
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 (2018)
Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) (2018)
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) (2018)
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)
Peter Henderson, Joshua Romoff, Joelle Pineau
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods. CoRR (2018)
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
An Introduction to Deep Reinforcement Learning. CoRR (2018)
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 (2017)
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 (2017)
Peter Henderson, Matthew Vertescher
An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models. CoRR (2017)
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)
Peter Henderson, Matthew Vertescher, David Meger, Mark Coates
Cost Adaptation for Robust Decentralized Swarm Behaviour. CoRR (2017)
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger
Deep Reinforcement Learning that Matters. CoRR (2017)
Peter Henderson, Wei-Di Chang, Florian Shkurti, Johanna Hansen, David Meger, Gregory Dudek
Benchmark Environments for Multitask Learning in Continuous Domains. CoRR (2017)
Maryam Fazel-Zarandi, Shang-Wen Li, Jin Cao, Jared Casale, Peter Henderson, David Whitney, Alborz Geramifard
Learning Robust Dialog Policies in Noisy Environments. CoRR (2017)
Peter Henderson, Thang Doan, Riashat Islam, David Meger
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR (2017)
Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau
Ethical Challenges in Data-Driven Dialogue Systems. CoRR (2017)
Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. CoRR (2017)
Peter Henderson, Muthucumaru Maheswaran
Chaotic Memory Randomization for Securing Embedded Systems. CoRR (2016)
Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau
A Survey of Available Corpora for Building Data-Driven Dialogue Systems. CoRR (2015)