Whole-Chain Recommendations-Reference-Cited by-同舟云学术

Whole-Chain Recommendations

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Information & Knowledge Management
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Author:

Zhao Xiangyu¹,Xia Long²,Zou Lixin³,Liu Hui¹,Yin Dawei⁴,Tang Jiliang¹

Affiliation:

1. Michigan State University, East Lansing, MI, USA

2. York University, Toronto, ON, Canada

3. Baidu Inc., Beijing, China

4. Baidu, Beijing, China

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3340531.3412044

Reference40 articles.

1. R-max-a general polynomial time algorithm for near-optimal reinforcement learning;Brafman Ronen I;Journal of Machine Learning Research,2002

2. Reinforcement Mechanism Design for e-commerce

3. Haokun Chen Xinyi Dai Han Cai Weinan Zhang Xuejian Wang Ruiming Tang Yuzhou Zhang and Yong Yu. 2018b. Large-scale Interactive Recommendation with Tree-structured Policy Gradient. arXiv preprint arXiv:1811.05869 (2018). Haokun Chen Xinyi Dai Han Cai Weinan Zhang Xuejian Wang Ruiming Tang Yuzhou Zhang and Yong Yu. 2018b. Large-scale Interactive Recommendation with Tree-structured Policy Gradient. arXiv preprint arXiv:1811.05869 (2018).

4. Minmin Chen Alex Beutel Paul Covington Sagar Jain Francois Belletti and Ed Chi. 2018a. Top-K Off-Policy Correction for a REINFORCE Recommender System. arXiv preprint arXiv:1812.02353 (2018). Minmin Chen Alex Beutel Paul Covington Sagar Jain Francois Belletti and Ed Chi. 2018a. Top-K Off-Policy Correction for a REINFORCE Recommender System. arXiv preprint arXiv:1812.02353 (2018).

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