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  Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation

Lu, C., Huang, B., Wang, K., Hernández-Lobato, J. M., Zhang, K., & Schölkopf, B. (2020). Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation. Retrieved from https://offline-rl-neurips.github.io/program/offrl_34.html.

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 Creators:
Lu, Chaochao1, 2, Author           
Huang, Biwei1, Author
Wang, Ke1, Author
Hernández-Lobato, José Miguel1, Author
Zhang, Kun1, Author
Schölkopf, Bernhard2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
 Abstract: -

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published online
 Pages: 14
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Luetal20
URI: https://offline-rl-neurips.github.io/program/offrl_34.html
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Title: Offline Reinforcement Learning Workshop
Place of Event: Online
Start-/End Date: 2020-12-12 - 2020-12-12

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Title: Offline Reinforcement Learning Workshop
  Subtitle : Workshop at Reinforcement Learning Workshop Neural Information Processing Systems, 2020
Source Genre: Web Page
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: URI: https://offline-rl-neurips.github.io/papers.html