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@STRING{lncs	= {Lecture Notes in Computer Science} }
@STRING{mathcomp= {Math. of Computation} }
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@STRING{mitai	= {Artificial Intelligence Laboratory, Massachusetts
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@STRING{neurips  = nips }
@STRING{nips	= {Advances in Neural Information Processing Systems (NeurIPS)} }
@STRING{nips1	= {Advances in Neural Information Processing Systems 1} }
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@STRING{nips10e	= {M.~I. Jordan and M.~J. Kearns and S.~A. Solla} }
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@STRING{nips11e	= {M.~S. Kearns and S.~A. Solla and D.~A. Cohn} }
@STRING{nips12	= {Advances in Neural Information Processing Systems 12} }
@STRING{nips12e	= {S.~A. Solla and T.~K. Leen and K.-R. M\"uller} }
@STRING{nips13	= {Advances in Neural Information Processing Systems 13} }
@STRING{nips13e	= {T.~K. Leen and T.~G. Dietterich and V. Tresp} }
@STRING{nips14	= {Advances in Neural Information Processing Systems 14} }
@STRING{nips14e	= {T.~G. Dietterich and S. Becker and Z. Ghahramani} }
@STRING{nips15	= {Advances in Neural Information Processing Systems 15} }
@STRING{nips15e	= {S. Becker and S. Thrun and K. Obermayer} }
@STRING{nips16	= {Advances in Neural Information Processing Systems 16} }
@STRING{nips16e	= {S. Thrun and L. Saul and B. Sch\"olkopf} }
@STRING{nips17	= {Advances in Neural Information Processing Systems 17} }
@STRING{nips17e	= {L. K. Saul and Y. Weiss and L. Bottou} }
@STRING{nips18	= {Advances in Neural Information Processing Systems 18} }
@STRING{nips18e	= {Y. Weiss and B. Sch\"olkopf and J. Platt} }
@STRING{nips19	= {Advances in Neural Information Processing Systems 19} }
@STRING{nips19e	= {B. Sch\"olkopf and J. Platt and T. Hofmann} }
@STRING{nips1e	= {D.~S. Touretzky} }
@STRING{nips2	= {Advances in Neural Information Processing Systems 2} }
@STRING{nips20	= {Advances in Neural Information Processing Systems 20} }
@STRING{nips20e	= {J.~C. Platt and D. Koller and Y. Singer and S. Roweis} }
@STRING{nips21	= {Advances in Neural Information Processing Systems 21} }
@STRING{nips21e	= {D. Koller and Y. Bengio and D. Schuurmans and L. Bottou
		  and A. Culotta} }
@STRING{nips22	= {Advances in Neural Information Processing Systems 22} }
@STRING{nips22e	= {Yoshua Bengio and Dale Schuurmans and John Lafferty and
		  Chris Williams and Alan Culota} }
@STRING{nips23	= {Advances in Neural Information Processing Systems 23} }
@STRING{nips23e	= {Richard Zemel and John Shawe-Taylor and John Lafferty and
		  Chris Williams and Alan Culota} }
@STRING{nips24	= {Advances in Neural Information Processing Systems 24} }
@STRING{nips2e	= {D.~S. Touretzky} }
@STRING{nips3	= {Advances in Neural Information Processing Systems 3} }
@STRING{nips3e	= {R. Lippmann and J.~E. Moody and D.~S. Touretzky} }
@STRING{nips4	= {Advances in Neural Information Processing Systems 4} }
@STRING{nips4e	= {J.~E. Moody and S.~J. Hanson and R. Lippmann} }
@STRING{nips5	= {Advances in Neural Information Processing Systems 5} }
@STRING{nips5e	= {S.~J. Hanson and J.~D. Cowan and C.~L. Giles} }
@STRING{nips6	= {Advances in Neural Information Processing Systems 6} }
@STRING{nips6e	= {J.~D. Cowan and G. Tesauro and J. Alspector} }
@STRING{nips7	= {Advances in Neural Information Processing Systems 7} }
@STRING{nips7e	= {G. Tesauro and D.~S. Touretzky and T.~K. Leen} }
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@STRING{nips8e	= {D.~S. Touretzky and M.~C. Mozer and M.~E. Hasselmo} }
@STRING{nips9	= {Advances in Neural Information Processing Systems 9} }
@STRING{nips9e	= {M.~C. Mozer and M.~I. Jordan and T. Petsche} }
@STRING{nips_short={NIPS} }
@STRING{nn	= {Neural Networks} }
@STRING{ny	= {New York} }
@STRING{opteng	= {Optical Engineering} }
@STRING{pami	= {IEEE Transactions on Pattern Analysis and Machine
		  Intelligence} }
@STRING{patt	= {Proc.\ Intl.\ Conf.\ Pattern Recognition} }
@STRING{pnas	= {Proc.\ Natl.\ Acad.\ Sci.\ USA} }
@STRING{pr	= {Pattern Recognition} }
@STRING{prip	= {Proceedings of IEEE Computer Society Conference on Pattern
		  Recognition and Image Processing} }
@STRING{prsl	= {Proceedings of the Royal Society of London} }
@STRING{prslb	= {Proceedings of the Royal Society of London B} }
@STRING{recsys	= recsys_long }
@STRING{recsys_short={RecSys} }
@STRING{robau	= {Proceedings of IEEE Conference on Robotics and
		  Automation} }
@STRING{sciam	= {Scientific American} }
@STRING{siam	= {SIAM J. Comp.} }
@STRING{siamopt	= {SIAM Journal on Optimization} }
@STRING{siamstat= {SIAM J.\ on Scientific and Statistical Computing} }
@STRING{sigir	= sigir_long }
@STRING{sigir_short={SIRIR} }
@STRING{sml	= {Statistical Machine Learning Program} }
@STRING{spring	= {Springer} }
@STRING{stoc	= {Proceedings ACM Symposium on Theory of Computing (STOC)} }
@STRING{tams	= {Transactions of the American Mathematical Society} }
@STRING{theoprob= {Theory of Probability and its Applications} }
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@STRING{uai_short={UAI} }
@STRING{visres	= {Vision Research} }
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@STRING{www	= www_long }
@STRING{www10	= {19th International Conference on the World Wide Web} }
@STRING{www11	= {20th International Conference on the World Wide Web} }
@STRING{www11e	= {S. Srinivasan and K. Ramamritham and A. Kumar and M. P.
		  Ravindra and E. Bertino and R. Kumar} }
@STRING{www_short={WWW} }


@inproceedings{langley00,
 author    = {P. Langley},
 title     = {Crafting Papers on Machine Learning},
 year      = {2000},
 pages     = {1207--1216},
 editor    = {Pat Langley},
 booktitle     = {Proceedings of the 17th International Conference
              on Machine Learning (ICML 2000)},
 address   = {Stanford, CA},
 publisher = {Morgan Kaufmann}
}

@TechReport{mitchell80,
  author = 	 "T. M. Mitchell",
  title = 	 "The Need for Biases in Learning Generalizations",
  institution =  "Computer Science Department, Rutgers University",
  year = 	 "1980",
  address =	 "New Brunswick, MA",
}

@phdthesis{kearns89,
  author = {M. J. Kearns},
  title =  {Computational Complexity of Machine Learning},
  school = {Department of Computer Science, Harvard University},
  year =   {1989}
}

@Book{MachineLearningI,
  editor = 	 "R. S. Michalski and J. G. Carbonell and T.
		  M. Mitchell",
  title = 	 "Machine Learning: An Artificial Intelligence
		  Approach, Vol. I",
  publisher = 	 "Tioga",
  year = 	 "1983",
  address =	 "Palo Alto, CA"
}

@Book{DudaHart2nd,
  author =       "R. O. Duda and P. E. Hart and D. G. Stork",
  title =        "Pattern Classification",
  publisher =    "John Wiley and Sons",
  edition =      "2nd",
  year =         "2000"
}

@misc{anonymous,
  title= {Suppressed for Anonymity},
  author= {Author, N. N.},
  year= {2021}
}

@InCollection{Newell81,
  author =       "A. Newell and P. S. Rosenbloom",
  title =        "Mechanisms of Skill Acquisition and the Law of
                  Practice", 
  booktitle =    "Cognitive Skills and Their Acquisition",
  pages =        "1--51",
  publisher =    "Lawrence Erlbaum Associates, Inc.",
  year =         "1981",
  editor =       "J. R. Anderson",
  chapter =      "1",
  address =      "Hillsdale, NJ"
}


@Article{Samuel59,
  author = 	 "A. L. Samuel",
  title = 	 "Some Studies in Machine Learning Using the Game of
		  Checkers",
  journal =	 "IBM Journal of Research and Development",
  year =	 "1959",
  volume =	 "3",
  number =	 "3",
  pages =	 "211--229"
}
@inproceedings{Xu2021Transferable,
  author       = {Hang Xu and
                  Rundong Wang and
                  Lev Raizman and
                  Zinovi Rabinovich},
  editor       = {Frank Dignum and
                  Alessio Lomuscio and
                  Ulle Endriss and
                  Ann Now{\'{e}}},
  title        = {Transferable Environment Poisoning: Training-time Attack on Reinforcement
                  Learning},
  booktitle    = {{AAMAS} '21: 20th International Conference on Autonomous Agents and
                  Multiagent Systems, Virtual Event, United Kingdom, May 3-7, 2021},
  pages        = {1398--1406},
  publisher    = {{ACM}},
  year         = {2021},
  url          = {https://www.ifaamas.org/Proceedings/aamas2021/pdfs/p1398.pdf},
  doi          = {10.5555/3463952.3464113},
  timestamp    = {Wed, 20 Jul 2022 17:05:35 +0200},
  biburl       = {https://dblp.org/rec/conf/atal/XuWRR21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{Zhang2020Reward,
  author       = {Xuezhou Zhang and
                  Yuzhe Ma and
                  Adish Singla and
                  Xiaojin Zhu},
  title        = {Adaptive Reward-Poisoning Attacks against Reinforcement Learning},
  booktitle    = {Proceedings of the 37th International Conference on Machine Learning,
                  {ICML} 2020, 13-18 July 2020, Virtual Event},
  series       = {Proceedings of Machine Learning Research},
  volume       = {119},
  pages        = {11225--11234},
  publisher    = {{PMLR}},
  year         = {2020},
  url          = {http://proceedings.mlr.press/v119/zhang20u.html},
  timestamp    = {Thu, 14 Oct 2021 10:33:06 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/ZhangMS020.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@article{Rakhsha2021Reward,
  author       = {Amin Rakhsha and
                  Xuezhou Zhang and
                  Xiaojin Zhu and
                  Adish Singla},
  title        = {Reward Poisoning in Reinforcement Learning: Attacks Against Unknown
                  Learners in Unknown Environments},
  journal      = {CoRR},
  volume       = {abs/2102.08492},
  year         = {2021},
  url          = {https://arxiv.org/abs/2102.08492},
  eprinttype    = {arXiv},
  eprint       = {2102.08492},
  timestamp    = {Fri, 19 Feb 2021 11:02:14 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2102-08492.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Huang2019Deceptive,
  author       = {Yunhan Huang and
                  Quanyan Zhu},
  editor       = {Tansu Alpcan and
                  Yevgeniy Vorobeychik and
                  John S. Baras and
                  Gy{\"{o}}rgy D{\'{a}}n},
  title        = {Deceptive Reinforcement Learning Under Adversarial Manipulations on
                  Cost Signals},
  booktitle    = {Decision and Game Theory for Security - 10th International Conference,
                  GameSec 2019, Stockholm, Sweden, October 30 - November 1, 2019, Proceedings},
  series       = {Lecture Notes in Computer Science},
  volume       = {11836},
  pages        = {217--237},
  publisher    = {Springer},
  year         = {2019},
  url          = {https://doi.org/10.1007/978-3-030-32430-8\_14},
  doi          = {10.1007/978-3-030-32430-8\_14},
  timestamp    = {Thu, 07 Nov 2019 09:20:26 +0100},
  biburl       = {https://dblp.org/rec/conf/gamesec/HuangZ19a.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@book{Sutton1998RL,
  author       = {Richard S. Sutton and
                  Andrew G. Barto},
  title        = {Reinforcement learning - an introduction},
  series       = {Adaptive computation and machine learning},
  publisher    = {{MIT} Press},
  year         = {1998},
  url          = {https://www.worldcat.org/oclc/37293240},
  isbn         = {978-0-262-19398-6},
  timestamp    = {Fri, 17 Jul 2020 16:12:40 +0200},
  biburl       = {https://dblp.org/rec/books/lib/SuttonB98.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Levine2020Offline,
  author       = {Sergey Levine and
                  Aviral Kumar and
                  George Tucker and
                  Justin Fu},
  title        = {Offline Reinforcement Learning: Tutorial, Review, and Perspectives
                  on Open Problems},
  journal      = {CoRR},
  volume       = {abs/2005.01643},
  year         = {2020},
  url          = {https://arxiv.org/abs/2005.01643},
  eprinttype    = {arXiv},
  eprint       = {2005.01643},
  timestamp    = {Fri, 08 May 2020 15:04:04 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2005-01643.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Fu2020d4rl,
  author       = {Justin Fu and
                  Aviral Kumar and
                  Ofir Nachum and
                  George Tucker and
                  Sergey Levine},
  title        = {{D4RL:} Datasets for Deep Data-Driven Reinforcement Learning},
  journal      = {CoRR},
  volume       = {abs/2004.07219},
  year         = {2020},
  url          = {https://arxiv.org/abs/2004.07219},
  eprinttype    = {arXiv},
  eprint       = {2004.07219},
  timestamp    = {Tue, 21 Apr 2020 16:51:52 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2004-07219.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Gong2022BackdoorORL,
  author       = {Chen Gong and
                  Zhou Yang and
                  Yunpeng Bai and
                  Junda He and
                  Jieke Shi and
                  Arunesh Sinha and
                  Bowen Xu and
                  Xinwen Hou and
                  Guoliang Fan and
                  David Lo},
  title        = {Mind Your Data! Hiding Backdoors in Offline Reinforcement Learning
                  Datasets},
  journal      = {CoRR},
  volume       = {abs/2210.04688},
  year         = {2022},
  url          = {https://doi.org/10.48550/arXiv.2210.04688},
  doi          = {10.48550/ARXIV.2210.04688},
  eprinttype    = {arXiv},
  eprint       = {2210.04688},
  timestamp    = {Tue, 23 May 2023 16:45:19 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2210-04688.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Huang2017AdvRL,
  author       = {Sandy H. Huang and
                  Nicolas Papernot and
                  Ian J. Goodfellow and
                  Yan Duan and
                  Pieter Abbeel},
  title        = {Adversarial Attacks on Neural Network Policies},
  booktitle    = {5th International Conference on Learning Representations, {ICLR} 2017,
                  Toulon, France, April 24-26, 2017, Workshop Track Proceedings},
  publisher    = {OpenReview.net},
  year         = {2017},
  url          = {https://openreview.net/forum?id=ryvlRyBKl},
  timestamp    = {Tue, 24 Sep 2019 17:13:20 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/HuangPGDA17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{Sun2020AdvRL,
  author       = {Jianwen Sun and
                  Tianwei Zhang and
                  Xiaofei Xie and
                  Lei Ma and
                  Yan Zheng and
                  Kangjie Chen and
                  Yang Liu},
  title        = {Stealthy and Efficient Adversarial Attacks against Deep Reinforcement
                  Learning},
  booktitle    = {The Thirty-Fourth {AAAI} Conference on Artificial Intelligence, {AAAI}
                  2020, The Thirty-Second Innovative Applications of Artificial Intelligence
                  Conference, {IAAI} 2020, The Tenth {AAAI} Symposium on Educational
                  Advances in Artificial Intelligence, {EAAI} 2020, New York, NY, USA,
                  February 7-12, 2020},
  pages        = {5883--5891},
  publisher    = {{AAAI} Press},
  year         = {2020},
  url          = {https://doi.org/10.1609/aaai.v34i04.6047},
  doi          = {10.1609/AAAI.V34I04.6047},
  timestamp    = {Mon, 04 Sep 2023 16:50:27 +0200},
  biburl       = {https://dblp.org/rec/conf/aaai/SunZX0ZCL20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Haarnoja2017SAC,
  author       = {Tuomas Haarnoja and
                  Haoran Tang and
                  Pieter Abbeel and
                  Sergey Levine},
  editor       = {Doina Precup and
                  Yee Whye Teh},
  title        = {Reinforcement Learning with Deep Energy-Based Policies},
  booktitle    = {Proceedings of the 34th International Conference on Machine Learning,
                  {ICML} 2017, Sydney, NSW, Australia, 6-11 August 2017},
  series       = {Proceedings of Machine Learning Research},
  volume       = {70},
  pages        = {1352--1361},
  publisher    = {{PMLR}},
  year         = {2017},
  url          = {http://proceedings.mlr.press/v70/haarnoja17a.html},
  timestamp    = {Wed, 29 May 2019 08:41:45 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/HaarnojaTAL17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Kumar2020CQL,
  author       = {Aviral Kumar and
                  Aurick Zhou and
                  George Tucker and
                  Sergey Levine},
  editor       = {Hugo Larochelle and
                  Marc'Aurelio Ranzato and
                  Raia Hadsell and
                  Maria{-}Florina Balcan and
                  Hsuan{-}Tien Lin},
  title        = {Conservative Q-Learning for Offline Reinforcement Learning},
  booktitle    = {Advances in Neural Information Processing Systems 33: Annual Conference
                  on Neural Information Processing Systems 2020, NeurIPS 2020, December
                  6-12, 2020, virtual},
  year         = {2020},
  url          = {https://proceedings.neurips.cc/paper/2020/hash/0d2b2061826a5df3221116a5085a6052-Abstract.html},
  timestamp    = {Tue, 19 Jan 2021 15:57:33 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/KumarZTL20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Kostrikov2022IQL,
  author       = {Ilya Kostrikov and
                  Ashvin Nair and
                  Sergey Levine},
  title        = {Offline Reinforcement Learning with Implicit Q-Learning},
  booktitle    = {The Tenth International Conference on Learning Representations, {ICLR}
                  2022, Virtual Event, April 25-29, 2022},
  publisher    = {OpenReview.net},
  year         = {2022},
  url          = {https://openreview.net/forum?id=68n2s9ZJWF8},
  timestamp    = {Sat, 20 Aug 2022 01:15:42 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/KostrikovNL22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{Yu2023Actor,
  author       = {Zishun Yu and
                  Xinhua Zhang},
  editor       = {Andreas Krause and
                  Emma Brunskill and
                  Kyunghyun Cho and
                  Barbara Engelhardt and
                  Sivan Sabato and
                  Jonathan Scarlett},
  title        = {Actor-Critic Alignment for Offline-to-Online Reinforcement Learning},
  booktitle    = {International Conference on Machine Learning, {ICML} 2023, 23-29 July
                  2023, Honolulu, Hawaii, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {202},
  pages        = {40452--40474},
  publisher    = {{PMLR}},
  year         = {2023},
  url          = {https://proceedings.mlr.press/v202/yu23k.html},
  timestamp    = {Mon, 28 Aug 2023 17:23:09 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/YuZ23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Geiping2021witchesBrew,
  author    = {Jonas Geiping and
               Liam H. Fowl and
               W. Ronny Huang and
               Wojciech Czaja and
               Gavin Taylor and
               Michael Moeller and
               Tom Goldstein},
  title     = {Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching},
  booktitle = {9th International Conference on Learning Representations, {ICLR} 2021,
               Virtual Event, Austria, May 3-7, 2021},
  publisher = {OpenReview.net},
  year      = {2021},
  url       = {https://openreview.net/forum?id=01olnfLIbD},
  timestamp = {Wed, 23 Jun 2021 17:36:39 +0200},
  biburl    = {https://dblp.org/rec/conf/iclr/GeipingFHCT0G21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Kang2023CIAP,
  author       = {Siteng Kang and
                  Zhan Shi and
                  Xinhua Zhang},
  editor       = {Andreas Krause and
                  Emma Brunskill and
                  Kyunghyun Cho and
                  Barbara Engelhardt and
                  Sivan Sabato and
                  Jonathan Scarlett},
  title        = {Poisoning Generative Replay in Continual Learning to Promote Forgetting},
  booktitle    = {International Conference on Machine Learning, {ICML} 2023, 23-29 July
                  2023, Honolulu, Hawaii, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {202},
  pages        = {15769--15785},
  publisher    = {{PMLR}},
  year         = {2023},
  url          = {https://proceedings.mlr.press/v202/kang23c.html},
  timestamp    = {Mon, 28 Aug 2023 17:23:08 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/KangSZ23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@inproceedings{Laroche2019safe,
  author       = {Romain Laroche and
                  Paul Trichelair and
                  Remi Tachet des Combes},
  editor       = {Kamalika Chaudhuri and
                  Ruslan Salakhutdinov},
  title        = {Safe Policy Improvement with Baseline Bootstrapping},
  booktitle    = {Proceedings of the 36th International Conference on Machine Learning,
                  {ICML} 2019, 9-15 June 2019, Long Beach, California, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {97},
  pages        = {3652--3661},
  publisher    = {{PMLR}},
  year         = {2019},
  url          = {http://proceedings.mlr.press/v97/laroche19a.html},
  timestamp    = {Tue, 11 Jun 2019 15:37:38 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/LarocheTC19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{Bengio2000Gradient,
  author       = {Yoshua Bengio},
  title        = {Gradient-Based Optimization of Hyperparameters},
  journal      = {Neural Comput.},
  volume       = {12},
  number       = {8},
  pages        = {1889--1900},
  year         = {2000},
  url          = {https://doi.org/10.1162/089976600300015187},
  doi          = {10.1162/089976600300015187},
  timestamp    = {Tue, 01 Sep 2020 13:12:04 +0200},
  biburl       = {https://dblp.org/rec/journals/neco/Bengio00.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Maclaurin2015Gradient,
  author       = {Dougal Maclaurin and
                  David Duvenaud and
                  Ryan P. Adams},
  editor       = {Francis R. Bach and
                  David M. Blei},
  title        = {Gradient-based Hyperparameter Optimization through Reversible Learning},
  booktitle    = {Proceedings of the 32nd International Conference on Machine Learning,
                  {ICML} 2015, Lille, France, 6-11 July 2015},
  series       = {{JMLR} Workshop and Conference Proceedings},
  volume       = {37},
  pages        = {2113--2122},
  publisher    = {JMLR.org},
  year         = {2015},
  url          = {http://proceedings.mlr.press/v37/maclaurin15.html},
  timestamp    = {Mon, 22 Jul 2019 14:09:24 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/MaclaurinDA15.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Shaban2019Truncated,
  author       = {Amirreza Shaban and
                  Ching{-}An Cheng and
                  Nathan Hatch and
                  Byron Boots},
  editor       = {Kamalika Chaudhuri and
                  Masashi Sugiyama},
  title        = {Truncated Back-propagation for Bilevel Optimization},
  booktitle    = {The 22nd International Conference on Artificial Intelligence and Statistics,
                  {AISTATS} 2019, 16-18 April 2019, Naha, Okinawa, Japan},
  series       = {Proceedings of Machine Learning Research},
  volume       = {89},
  pages        = {1723--1732},
  publisher    = {{PMLR}},
  year         = {2019},
  url          = {http://proceedings.mlr.press/v89/shaban19a.html},
  timestamp    = {Fri, 07 Jun 2019 09:03:47 +0200},
  biburl       = {https://dblp.org/rec/conf/aistats/ShabanCHB19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Lorraine2020Opt,
  author       = {Jonathan Lorraine and
                  Paul Vicol and
                  David Duvenaud},
  editor       = {Silvia Chiappa and
                  Roberto Calandra},
  title        = {Optimizing Millions of Hyperparameters by Implicit Differentiation},
  booktitle    = {The 23rd International Conference on Artificial Intelligence and Statistics,
                  {AISTATS} 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy]},
  series       = {Proceedings of Machine Learning Research},
  volume       = {108},
  pages        = {1540--1552},
  publisher    = {{PMLR}},
  year         = {2020},
  url          = {http://proceedings.mlr.press/v108/lorraine20a.html},
  timestamp    = {Mon, 29 Jun 2020 18:03:58 +0200},
  biburl       = {https://dblp.org/rec/conf/aistats/LorraineVD20.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{Haarnoja2018sac,
  author       = {Tuomas Haarnoja and
                  Aurick Zhou and
                  Kristian Hartikainen and
                  George Tucker and
                  Sehoon Ha and
                  Jie Tan and
                  Vikash Kumar and
                  Henry Zhu and
                  Abhishek Gupta and
                  Pieter Abbeel and
                  Sergey Levine},
  title        = {Soft Actor-Critic Algorithms and Applications},
  journal      = {CoRR},
  volume       = {abs/1812.05905},
  year         = {2018},
  url          = {http://arxiv.org/abs/1812.05905},
  eprinttype    = {arXiv},
  eprint       = {1812.05905},
  timestamp    = {Tue, 01 Jan 2019 15:01:25 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1812-05905.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Wu2023Adv,
  author       = {Han Wu and
                  Syed Yunas and
                  Sareh Rowlands and
                  Wenjie Ruan and
                  Johan Wahlstr{\"{o}}m},
  title        = {Adversarial Driving: Attacking End-to-End Autonomous Driving},
  booktitle    = {{IEEE} Intelligent Vehicles Symposium, {IV} 2023, Anchorage, AK, USA,
                  June 4-7, 2023},
  pages        = {1--7},
  publisher    = {{IEEE}},
  year         = {2023},
  url          = {https://doi.org/10.1109/IV55152.2023.10186386},
  doi          = {10.1109/IV55152.2023.10186386},
  timestamp    = {Tue, 08 Aug 2023 10:24:13 +0200},
  biburl       = {https://dblp.org/rec/conf/ivs/WuYRRW23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{Rakhsha2021Policy,
  author       = {Amin Rakhsha and
                  Goran Radanovic and
                  Rati Devidze and
                  Xiaojin Zhu and
                  Adish Singla},
  title        = {Policy Teaching in Reinforcement Learning via Environment Poisoning
                  Attacks},
  journal      = {J. Mach. Learn. Res.},
  volume       = {22},
  pages        = {210:1--210:45},
  year         = {2021},
  url          = {http://jmlr.org/papers/v22/20-1329.html},
  timestamp    = {Mon, 31 Jan 2022 17:23:36 +0100},
  biburl       = {https://dblp.org/rec/journals/jmlr/RakhshaRDZS21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Wu2023Reward,
  author       = {Young Wu and
                  Jeremy McMahan and
                  Xiaojin Zhu and
                  Qiaomin Xie},
  editor       = {Brian Williams and
                  Yiling Chen and
                  Jennifer Neville},
  title        = {Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning},
  booktitle    = {Thirty-Seventh {AAAI} Conference on Artificial Intelligence, {AAAI}
                  2023, Thirty-Fifth Conference on Innovative Applications of Artificial
                  Intelligence, {IAAI} 2023, Thirteenth Symposium on Educational Advances
                  in Artificial Intelligence, {EAAI} 2023, Washington, DC, USA, February
                  7-14, 2023},
  pages        = {10426--10434},
  publisher    = {{AAAI} Press},
  year         = {2023},
  url          = {https://doi.org/10.1609/aaai.v37i9.26240},
  doi          = {10.1609/AAAI.V37I9.26240},
  timestamp    = {Mon, 04 Sep 2023 16:50:28 +0200},
  biburl       = {https://dblp.org/rec/conf/aaai/WuM0X23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Cheng2022Adv,
  author       = {Ching{-}An Cheng and
                  Tengyang Xie and
                  Nan Jiang and
                  Alekh Agarwal},
  editor       = {Kamalika Chaudhuri and
                  Stefanie Jegelka and
                  Le Song and
                  Csaba Szepesv{\'{a}}ri and
                  Gang Niu and
                  Sivan Sabato},
  title        = {Adversarially Trained Actor Critic for Offline Reinforcement Learning},
  booktitle    = {International Conference on Machine Learning, {ICML} 2022, 17-23 July
                  2022, Baltimore, Maryland, {USA}},
  series       = {Proceedings of Machine Learning Research},
  volume       = {162},
  pages        = {3852--3878},
  publisher    = {{PMLR}},
  year         = {2022},
  url          = {https://proceedings.mlr.press/v162/cheng22b.html},
  timestamp    = {Tue, 12 Jul 2022 17:36:52 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/ChengX0A22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Ma2019Policy,
  author       = {Yuzhe Ma and
                  Xuezhou Zhang and
                  Wen Sun and
                  Jerry Zhu},
  editor       = {Hanna M. Wallach and
                  Hugo Larochelle and
                  Alina Beygelzimer and
                  Florence d'Alch{\'{e}}{-}Buc and
                  Emily B. Fox and
                  Roman Garnett},
  title        = {Policy Poisoning in Batch Reinforcement Learning and Control},
  booktitle    = {Advances in Neural Information Processing Systems 32: Annual Conference
                  on Neural Information Processing Systems 2019, NeurIPS 2019, December
                  8-14, 2019, Vancouver, BC, Canada},
  pages        = {14543--14553},
  year         = {2019},
  url          = {https://proceedings.neurips.cc/paper/2019/hash/315f006f691ef2e689125614ea22cc61-Abstract.html},
  timestamp    = {Sun, 05 Feb 2023 21:02:53 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/MaZSZ19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Goodfellow2014Adv,
  author       = {Ian J. Goodfellow and
                  Jonathon Shlens and
                  Christian Szegedy},
  editor       = {Yoshua Bengio and
                  Yann LeCun},
  title        = {Explaining and Harnessing Adversarial Examples},
  booktitle    = {3rd International Conference on Learning Representations, {ICLR} 2015,
                  San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings},
  year         = {2015},
  url          = {http://arxiv.org/abs/1412.6572},
  timestamp    = {Thu, 25 Jul 2019 14:25:38 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/GoodfellowSS14.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}



@article{Goldblum2023survey,
  author       = {Micah Goldblum and
                  Dimitris Tsipras and
                  Chulin Xie and
                  Xinyun Chen and
                  Avi Schwarzschild and
                  Dawn Song and
                  Aleksander Madry and
                  Bo Li and
                  Tom Goldstein},
  title        = {Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks,
                  and Defenses},
  journal      = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
  volume       = {45},
  number       = {2},
  pages        = {1563--1580},
  year         = {2023},
  url          = {https://doi.org/10.1109/TPAMI.2022.3162397},
  doi          = {10.1109/TPAMI.2022.3162397},
  timestamp    = {Mon, 28 Aug 2023 21:37:38 +0200},
  biburl       = {https://dblp.org/rec/journals/pami/GoldblumTXCSSML23.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Cherepanova2021Lowkey,
  author       = {Valeriia Cherepanova and
                  Micah Goldblum and
                  Harrison Foley and
                  Shiyuan Duan and
                  John P. Dickerson and
                  Gavin Taylor and
                  Tom Goldstein},
  title        = {LowKey: Leveraging Adversarial Attacks to Protect Social Media Users
                  from Facial Recognition},
  booktitle    = {9th International Conference on Learning Representations, {ICLR} 2021,
                  Virtual Event, Austria, May 3-7, 2021},
  publisher    = {OpenReview.net},
  year         = {2021},
  url          = {https://openreview.net/forum?id=hJmtwocEqzc},
  timestamp    = {Wed, 23 Jun 2021 17:36:40 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/CherepanovaGFDD21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{Souri2022Sleeper,
  author       = {Hossein Souri and
                  Liam Fowl and
                  Rama Chellappa and
                  Micah Goldblum and
                  Tom Goldstein},
  editor       = {Sanmi Koyejo and
                  S. Mohamed and
                  A. Agarwal and
                  Danielle Belgrave and
                  K. Cho and
                  A. Oh},
  title        = {Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks
                  Trained from Scratch},
  booktitle    = {Advances in Neural Information Processing Systems 35: Annual Conference
                  on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans,
                  LA, USA, November 28 - December 9, 2022},
  year         = {2022},
  url          = {http://papers.nips.cc/paper\_files/paper/2022/hash/79eec295a3cd5785e18c61383e7c996b-Abstract-Conference.html},
  timestamp    = {Mon, 08 Jan 2024 16:31:37 +0100},
  biburl       = {https://dblp.org/rec/conf/nips/SouriFCGG22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}


@article{wu2019behavior,
  author       = {Yifan Wu and
                  George Tucker and
                  Ofir Nachum},
  title        = {Behavior Regularized Offline Reinforcement Learning},
  journal      = {CoRR},
  volume       = {abs/1911.11361},
  year         = {2019},
  url          = {http://arxiv.org/abs/1911.11361},
  eprinttype    = {arXiv},
  eprint       = {1911.11361},
  timestamp    = {Tue, 03 Dec 2019 14:15:54 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1911-11361.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{bai2022PBRL,
  author       = {Chenjia Bai and
                  Lingxiao Wang and
                  Zhuoran Yang and
                  Zhi{-}Hong Deng and
                  Animesh Garg and
                  Peng Liu and
                  Zhaoran Wang},
  title        = {Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement
                  Learning},
  booktitle    = {The Tenth International Conference on Learning Representations, {ICLR}
                  2022, Virtual Event, April 25-29, 2022},
  publisher    = {OpenReview.net},
  year         = {2022},
  url          = {https://openreview.net/forum?id=Y4cs1Z3HnqL},
  timestamp    = {Wed, 27 Dec 2023 11:20:17 +0100},
  biburl       = {https://dblp.org/rec/conf/iclr/Bai0YDG0W22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}




#################################
# bib item added by Zishun
#################################

@INPROCEEDINGS{mujoco,
  author={Todorov, Emanuel and Erez, Tom and Tassa, Yuval},
  booktitle={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems}, 
  title={MuJoCo: A physics engine for model-based control}, 
  year={2012},
  volume={},
  number={},
  pages={5026-5033},
  keywords={Engines;Optimization;Computational modeling;Heuristic algorithms;Dynamics;Mathematical model},
  doi={10.1109/IROS.2012.6386109}}


@InProceedings{lee2022offline,
  title = 	 {Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble},
  author =       {Lee, Seunghyun and Seo, Younggyo and Lee, Kimin and Abbeel, Pieter and Shin, Jinwoo},
  booktitle = 	 {Proceedings of the 5th Conference on Robot Learning},
  pages = 	 {1702--1712},
  year = 	 {2022},
  editor = 	 {Faust, Aleksandra and Hsu, David and Neumann, Gerhard},
  volume = 	 {164},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {08--11 Nov},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v164/lee22d/lee22d.pdf},
  url = 	 {https://proceedings.mlr.press/v164/lee22d.html},
}


@inproceedings{munos2005error,
author = {Munos, R\'{e}mi},
title = {Error bounds for approximate value iteration},
year = {2005},
isbn = {157735236x},
publisher = {AAAI Press},
booktitle = {Proceedings of the 20th National Conference on Artificial Intelligence - Volume 2},
pages = {1006–1011},
numpages = {6},
location = {Pittsburgh, Pennsylvania},
series = {AAAI'05},
url = {https://aaai.org/papers/01006-aaai05-159-error-bounds-for-approximate-value-iteration/},
}

@inproceedings{farahmand2010error,
 author = {Farahmand, Amir-massoud and Szepesv\'{a}ri, Csaba and Munos, R\'{e}mi},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {J. Lafferty and C. Williams and J. Shawe-Taylor and R. Zemel and A. Culotta},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Error Propagation for Approximate Policy and Value Iteration},
 url = {https://proceedings.neurips.cc/paper_files/paper/2010/file/65cc2c8205a05d7379fa3a6386f710e1-Paper.pdf},
 volume = {23},
 year = {2010}
}


@inproceedings{kumar20discor,
 author = {Kumar, Aviral and Gupta, Abhishek and Levine, Sergey},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {18560--18572},
 publisher = {Curran Associates, Inc.},
 title = {DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/d7f426ccbc6db7e235c57958c21c5dfa-Paper.pdf},
 volume = {33},
 year = {2020}
}


@InProceedings{fu2019disgnosing,
  title = 	 {Diagnosing Bottlenecks in Deep Q-learning Algorithms},
  author =       {Fu, Justin and Kumar, Aviral and Soh, Matthew and Levine, Sergey},
  booktitle = 	 {Proceedings of the 36th International Conference on Machine Learning},
  pages = 	 {2021--2030},
  year = 	 {2019},
  editor = 	 {Chaudhuri, Kamalika and Salakhutdinov, Ruslan},
  volume = 	 {97},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {09--15 Jun},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v97/fu19a/fu19a.pdf},
  url = 	 {https://proceedings.mlr.press/v97/fu19a.html},
}

@inproceedings{kumar2019stabilizing,
 author = {Kumar, Aviral and Fu, Justin and Soh, Matthew and Tucker, George and Levine, Sergey},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction},
 url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/c2073ffa77b5357a498057413bb09d3a-Paper.pdf},
 volume = {32},
 year = {2019}
}



@InProceedings{fujimoto2019offpolicy,
  title = 	 {Off-Policy Deep Reinforcement Learning without Exploration},
  author =       {Fujimoto, Scott and Meger, David and Precup, Doina},
  booktitle = 	 {Proceedings of the 36th International Conference on Machine Learning},
  pages = 	 {2052--2062},
  year = 	 {2019},
  editor = 	 {Chaudhuri, Kamalika and Salakhutdinov, Ruslan},
  volume = 	 {97},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {09--15 Jun},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v97/fujimoto19a/fujimoto19a.pdf},
  url = 	 {https://proceedings.mlr.press/v97/fujimoto19a.html},
}





# some additional O2O works


@inproceedings{wang2023train,
 author = {Wang, Shenzhi and Yang, Qisen and Gao, Jiawei and Lin, Matthieu and CHEN, HAO and Wu, Liwei and Jia, Ning and Song, Shiji and Huang, Gao},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {A. Oh and T. Naumann and A. Globerson and K. Saenko and M. Hardt and S. Levine},
 pages = {47081--47104},
 publisher = {Curran Associates, Inc.},
 title = {Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning},
 url = {https://proceedings.neurips.cc/paper_files/paper/2023/file/9318763d049edf9a1f2779b2a59911d3-Paper-Conference.pdf},
 volume = {36},
 year = {2023}
}


@inproceedings{
lei2023uni,
title={Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization},
author={Kun Lei and Zhengmao He and Chenhao Lu and Kaizhe Hu and Yang Gao and Huazhe Xu},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=tbFBh3LMKi}
}



@article{mark2023offline,
  title={Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias},
  author={Mark, Max Sobol and Sharma, Archit and Tajwar, Fahim and Rafailov, Rafael and Levine, Sergey and Finn, Chelsea},
  journal={arXiv preprint arXiv:2310.08558},
  year={2023},
  url={https://arxiv.org/abs/2310.08558}
}


@inproceedings{chen2023dcac,
author = {Chen, Dongxiang and Wen, Ying},
title = {DCAC: Reducing Unnecessary Conservatism in Offline-to-online Reinforcement Learning},
year = {2023},
isbn = {9798400708480},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3627676.3627677},
doi = {10.1145/3627676.3627677},
booktitle = {Proceedings of the Fifth International Conference on Distributed Artificial Intelligence},
articleno = {9},
numpages = {12},
keywords = {Finetune, Offline-to-online, Reinforcement Learning},
location = {<conf-loc>, <city>Singapore</city>, <country>Singapore</country>, </conf-loc>},
series = {DAI '23}
}


@inproceedings{wagenmaker2023leveraging,
author = {Wagenmaker, Andrew and Pacchiano, Aldo},
title = {Leveraging offline data in online reinforcement learning},
year = {2023},
publisher = {JMLR.org},
articleno = {1470},
numpages = {39},
location = {<conf-loc>, <city>Honolulu</city>, <state>Hawaii</state>, <country>USA</country>, </conf-loc>},
series = {ICML'23}
}



@inproceedings{
zhang2022policy,
title={Policy Expansion for Bridging Offline-to-Online Reinforcement Learning},
author={Haichao Zhang and Wei Xu and Haonan Yu},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=-Y34L45JR6z}
}





@article{nair2020awac,
  title={Awac: Accelerating online reinforcement learning with offline datasets},
  author={Nair, Ashvin and Gupta, Abhishek and Dalal, Murtaza and Levine, Sergey},
  journal={arXiv preprint arXiv:2006.09359},
  year={2020},
  url={https://arxiv.org/abs/2006.09359}
}

# ------------


@inproceedings{van2016deep,
author = {Hasselt, Hado van and Guez, Arthur and Silver, David},
title = {Deep reinforcement learning with double Q-Learning},
year = {2016},
publisher = {AAAI Press},
pages = {2094–2100},
numpages = {7},
location = {Phoenix, Arizona},
series = {AAAI'16}
}




@article{haarnoja2018soft,
  title={Soft actor-critic algorithms and applications},
  author={Haarnoja, Tuomas and Zhou, Aurick and Hartikainen, Kristian and Tucker, George and Ha, Sehoon and Tan, Jie and Kumar, Vikash and Zhu, Henry and Gupta, Abhishek and Abbeel, Pieter and others},
  journal={arXiv preprint arXiv:1812.05905},
  year={2018},
  url={https://arxiv.org/abs/1812.05905}
}


## Added for camera ready

@inproceedings{xie2021policy,
 author = {Xie, Tengyang and Jiang, Nan and Wang, Huan and Xiong, Caiming and Bai, Yu},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan},
 pages = {27395--27407},
 publisher = {Curran Associates, Inc.},
 title = {Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning},
 url = {https://proceedings.neurips.cc/paper_files/paper/2021/file/e61eaa38aed621dd776d0e67cfeee366-Paper.pdf},
 volume = {34},
 year = {2021}
}


@article{nakamoto2024cal,
  author       = {Mitsuhiko Nakamoto and Yuexiang Zhai and Anikait Singh and Max Sobol Mark and Yi Ma and Chelsea Finn and Aviral Kumar and Sergey Levine},
  title        = {Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning},
  conference   = {arXiv Pre-print},
  year         = {2023},
  url          = {https://arxiv.org/abs/2303.05479},
}



@misc{openaigym,
  Author = {Greg Brockman and Vicki Cheung and Ludwig Pettersson and Jonas Schneider and John Schulman and Jie Tang and Wojciech Zaremba},
  Title = {OpenAI Gym},
  Year = {2016},
  Eprint = {arXiv:1606.01540},
  url = {https://arxiv.org/abs/1606.01540}, 
}

@article{d3rlpy,
  author  = {Takuma Seno and Michita Imai},
  title   = {d3rlpy: An Offline Deep Reinforcement Learning Library},
  journal = {Journal of Machine Learning Research},
  year    = {2022},
  volume  = {23},
  number  = {315},
  pages   = {1--20},
  url     = {http://jmlr.org/papers/v23/22-0017.html}
}




---------------------

@article{Chen2017TargetedBA,
  title={Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning},
  author={X. Chen and Chang Liu and Bo Li and Kimberly Lu and D. Song},
  journal={ArXiv},
  year={2017},
  volume={abs/1712.05526}, 
  url={https://arxiv.org/abs/1712.05526}
}

@inproceedings{XiaXiaEck12,
author = {Xiao, Han and Xiao, Huang and Eckert, Claudia},
title = {Adversarial Label Flips Attack on Support Vector Machines},
year = {2012},
booktitle = {Proceedings of the 20th European Conference on Artificial Intelligence},
pages = {870–875},
numpages = {6},
url = {https://dl.acm.org/doi/abs/10.5555/3007337.3007488}, 
}

@inproceedings{
LevFei21,
title={Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks},
author={Alexander Levine and Soheil Feizi},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=YUGG2tFuPM}
}

@inproceedings{LevFei21,
  title={Deep Partition Aggregation: Provable Defense against General Poisoning Attacks},
  author={Alexander Levine and Soheil Feizi},
  booktitle=iclr,
  year={2021}
}

@inproceedings{Biggio2012PoisoningAA,
author = {Biggio, Battista and Nelson, Blaine and Laskov, Pavel},
title = {Poisoning attacks against support vector machines},
year = {2012},
isbn = {9781450312851},
publisher = {Omnipress},
address = {Madison, WI, USA},
pages = {1467–1474},
numpages = {8},
location = {Edinburgh, Scotland},
series = {ICML'12},
url={https://icml.cc/2012/papers/880.pdf}
}


@inproceedings{Shafahi2018PoisonFT,
 author = {Shafahi, Ali and Huang, W. Ronny and Najibi, Mahyar and Suciu, Octavian and Studer, Christoph and Dumitras, Tudor and Goldstein, Tom},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks},
 url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/22722a343513ed45f14905eb07621686-Paper.pdf},
 volume = {31},
 year = {2018}
}






--- online RL reward 

@inproceedings{banihashem2022admissible,
  title={Admissible policy teaching through reward design},
  author={Banihashem, Kiarash and Singla, Adish and Gan, Jiarui and Radanovic, Goran},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={36},
  number={6},
  pages={6037--6045},
  year={2022}
}

@inproceedings{liu2024efficient,
 author = {Liu, Guanlin and Lai, Lifeng},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {A. Oh and T. Naumann and A. Globerson and K. Saenko and M. Hardt and S. Levine},
 pages = {24401--24433},
 publisher = {Curran Associates, Inc.},
 title = {Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning},
 url = {https://proceedings.neurips.cc/paper_files/paper/2023/file/4cddc8fc57039f8fe44e23aba1e4df40-Paper-Conference.pdf},
 volume = {36},
 year = {2023}
}

@inproceedings{
sun2020vulnerability,
title={Vulnerability-Aware Poisoning Mechanism for Online {\{}RL{\}} with Unknown Dynamics},
author={Yanchao Sun and Da Huo and Furong Huang},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=9r30XCjf5Dt}
}



@InProceedings{zhang2020adaptive,
  title = 	 {Adaptive Reward-Poisoning Attacks against Reinforcement Learning},
  author =       {Zhang, Xuezhou and Ma, Yuzhe and Singla, Adish and Zhu, Xiaojin},
  booktitle = 	 {Proceedings of the 37th International Conference on Machine Learning},
  pages = 	 {11225--11234},
  year = 	 {2020},
  editor = 	 {III, Hal Daumé and Singh, Aarti},
  volume = 	 {119},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {13--18 Jul},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v119/zhang20u/zhang20u.pdf},
  url = 	 {https://proceedings.mlr.press/v119/zhang20u.html},
}






----- online bandits


@InProceedings{bogunovic2021stochastic,
  title = 	 { Stochastic Linear Bandits Robust to Adversarial Attacks },
  author =       {Bogunovic, Ilija and Losalka, Arpan and Krause, Andreas and Scarlett, Jonathan},
  booktitle = 	 {Proceedings of The 24th International Conference on Artificial Intelligence and Statistics},
  pages = 	 {991--999},
  year = 	 {2021},
  editor = 	 {Banerjee, Arindam and Fukumizu, Kenji},
  volume = 	 {130},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {13--15 Apr},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v130/bogunovic21a/bogunovic21a.pdf},
  url = 	 {https://proceedings.mlr.press/v130/bogunovic21a.html},
}


@inproceedings{garcelon2020adversarial,
 author = {Garcelon, Evrard and Roziere, Baptiste and Meunier, Laurent and Tarbouriech, Jean and Teytaud, Olivier and Lazaric, Alessandro and Pirotta, Matteo},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {14362--14373},
 publisher = {Curran Associates, Inc.},
 title = {Adversarial Attacks on Linear Contextual Bandits},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/a554f89dd61cabd2ff833d3468e2008a-Paper.pdf},
 volume = {33},
 year = {2020}
}


@inproceedings{guan2020robust,
  title={Robust stochastic bandit algorithms under probabilistic unbounded adversarial attack},
  author={Guan, Ziwei and Ji, Kaiyi and Bucci Jr, Donald J and Hu, Timothy Y and Palombo, Joseph and Liston, Michael and Liang, Yingbin},
  booktitle={Proceedings of the aaai conference on artificial intelligence},
  volume={34},
  number={04},
  pages={4036--4043},
  year={2020},
}

@inproceedings{jun2018adversarial,
 author = {Jun, Kwang-Sung and Li, Lihong and Ma, Yuzhe and Zhu, Jerry},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Adversarial Attacks on Stochastic Bandits},
 url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/85f007f8c50dd25f5a45fca73cad64bd-Paper.pdf},
 volume = {31},
 year = {2018}
}


@InProceedings{liu2019data,
  title = 	 {Data Poisoning Attacks on Stochastic Bandits},
  author =       {Liu, Fang and Shroff, Ness},
  booktitle = 	 {Proceedings of the 36th International Conference on Machine Learning},
  pages = 	 {4042--4050},
  year = 	 {2019},
  editor = 	 {Chaudhuri, Kamalika and Salakhutdinov, Ruslan},
  volume = 	 {97},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {09--15 Jun},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v97/liu19e/liu19e.pdf},
  url = 	 {https://proceedings.mlr.press/v97/liu19e.html},
}


@inproceedings{lu2021stochastic,
  title={Stochastic graphical bandits with adversarial corruptions},
  author={Lu, Shiyin and Wang, Guanghui and Zhang, Lijun},
  booktitle={Proceedings of the aaai conference on artificial intelligence},
  volume={35},
  number={10},
  pages={8749--8757},
  year={2021}
}

@inproceedings{ma2018data,
  title={Data poisoning attacks in contextual bandits},
  author={Ma, Yuzhe and Jun, Kwang-Sung and Li, Lihong and Zhu, Xiaojin},
  booktitle={Decision and Game Theory for Security: 9th International Conference, GameSec 2018, Seattle, WA, USA, October 29--31, 2018, Proceedings 9},
  pages={186--204},
  year={2018},
  organization={Springer}
}

@inproceedings{hajiesmaili2020adversarial,
 author = {yang, lin and Hajiesmaili, Mohammad and Talebi, Mohammad Sadegh and Lui, John C. S. and Wong, Wing Shing},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {19943--19952},
 publisher = {Curran Associates, Inc.},
 title = {Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/e655c7716a4b3ea67f48c6322fc42ed6-Paper.pdf},
 volume = {33},
 year = {2020}
}


@article{zuo2020near,
  title={Near optimal adversarial attack on UCB bandits},
  author={Zuo, Shiliang},
  journal={arXiv preprint arXiv:2008.09312},
  year={2020},
  url={https://arxiv.org/abs/2008.09312}
}





-- offline rl reward


@inproceedings{rangi2022understanding,
  title     = {Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning},
  author    = {Rangi, Anshuka and Xu, Haifeng and Tran-Thanh, Long and Franceschetti, Massimo},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {3394--3400},
  year      = {2022},
  month     = {7},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2022/471},
  url       = {https://doi.org/10.24963/ijcai.2022/471},
}





@inproceedings{zhang2008value,
  title={Value-Based Policy Teaching with Active Indirect Elicitation.},
  author={Zhang, Haoqi and Parkes, David C},
  booktitle={AAAI},
  volume={8},
  pages={208--214},
  year={2008}
}

@inproceedings{zhang2009policy,
  title={Policy teaching through reward function learning},
  author={Zhang, Haoqi and Parkes, David C and Chen, Yiling},
  booktitle={Proceedings of the 10th ACM conference on Electronic commerce},
  pages={295--304},
  year={2009}
}

--- defense against rl

@article{
banihashem2021defense,
title={Defense Against Reward Poisoning Attacks in Reinforcement Learning},
author={Kiarash Banihashem and Adish Singla and Goran Radanovic},
journal={Transactions on Machine Learning Research},
issn={2835-8856},
year={2023},
url={https://openreview.net/forum?id=goPsLn3RVo},
note={}
}



@InProceedings{lykouris2021corruption,
  title = 	 {Corruption-robust exploration in episodic reinforcement learning},
  author =       {Lykouris, Thodoris and Simchowitz, Max and Slivkins, Alex and Sun, Wen},
  booktitle = 	 {Proceedings of Thirty Fourth Conference on Learning Theory},
  pages = 	 {3242--3245},
  year = 	 {2021},
  editor = 	 {Belkin, Mikhail and Kpotufe, Samory},
  volume = 	 {134},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {15--19 Aug},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v134/lykouris21a/lykouris21a.pdf},
  url = 	 {https://proceedings.mlr.press/v134/lykouris21a.html},
}





@inproceedings{rangi2022saving,
  title={Saving stochastic bandits from poisoning attacks via limited data verification},
  author={Rangi, Anshuka and Tran-Thanh, Long and Xu, Haifeng and Franceschetti, Massimo},
  booktitle={Proceedings of the aaai conference on artificial intelligence},
  volume={36},
  number={7},
  pages={8054--8061},
  year={2022}
}