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  Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning

Nika, A., Singla, A., & Radanovic, G. (2023). Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning. In F. Ruiz, J. Dy, & J.-W. van de Meent (Eds.), Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (pp. 335-358). PMRL.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-66DC-9 Version Permalink: https://hdl.handle.net/21.11116/0000-000E-7F47-5
Genre: Conference Paper

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 Creators:
Nika, Andi1, Author           
Singla, Adish1, Author                 
Radanovic, Goran2, Author           
Affiliations:
1Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society, ou_2541698              
2Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              

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Language(s): eng - English
 Dates: 20232023
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: NikaAISTATS23
URN: https://proceedings.mlr.press/v206/nika23a/nika23a.pdf
 Degree: -

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Title: 26th International Conference on Artificial Intelligence and Statistics
Place of Event: Valencia, Spain
Start-/End Date: 2023-04-25 - 2023-04-27

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Title: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics
  Abbreviation : AISTATS 2023
Source Genre: Proceedings
 Creator(s):
Ruiz, Francisco1, Editor
Dy, Jennifer1, Editor
van de Meent, Jan-Wilem1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: PMRL
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 335 - 358 Identifier: -

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Title: Proceedings of Machine Learning Research
Source Genre: Series
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Publ. Info: -
Pages: - Volume / Issue: 206 Sequence Number: - Start / End Page: - Identifier: -