Generative Slate Recommendation with Reinforcement Learning-Reference-Cited by-同舟云学术

Generative Slate Recommendation with Reinforcement Learning

Published:2023-02-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining
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Author:

Deffayet Romain¹^ORCID,Thonet Thibaut²^ORCID,Renders Jean-Michel²^ORCID,de Rijke Maarten³^ORCID

Affiliation:

1. Naver Labs Europe & University of Amsterdam, Meylan, France

2. Naver Labs Europe, Meylan, France

3. University of Amsterdam, Amsterdam, Netherlands

Funder

Hybrid Intelligence Center

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539597.3570412

Reference36 articles.

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2. Xueying Bai , Jian Guan , and Hongning Wang . 2019 . A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation . In NeurIPS '19 . 10734--10745. Xueying Bai, Jian Guan, and Hongning Wang. 2019. A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation. In NeurIPS '19. 10734--10745.

3. Eytan Bakshy , Solomon Messing , and Lada Adamic . 2015 . Exposure to Ideologically Diverse News and Opinion on Facebook . Science , Vol. 348 , 6239 (2015), 1130--1132. Eytan Bakshy, Solomon Messing, and Lada Adamic. 2015. Exposure to Ideologically Diverse News and Opinion on Facebook. Science, Vol. 348, 6239 (2015), 1130--1132.

4. Nicolò Botteghi , Mannes Poel , Beril Sirmacc ek, and Christoph Brune . 2021 . Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics . arXiv:2107.01677 (2021). Nicolò Botteghi, Mannes Poel, Beril Sirmacc ek, and Christoph Brune. 2021. Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics. arXiv:2107.01677 (2021).

5. Yash Chandak , Georgios Theocharous , James Kostas , Scott Jordan , and Philip Thomas . 2019 . Learning Action Representations for Reinforcement Learning. In ICML '19 . 941--950. Yash Chandak, Georgios Theocharous, James Kostas, Scott Jordan, and Philip Thomas. 2019. Learning Action Representations for Reinforcement Learning. In ICML '19. 941--950.

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