Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention
Author:
Affiliation:
1. City University of Hong Kong, Hong Kong, Hong Kong
2. Kuaishou Technology, Beijing, China
3. Unaffiliated, Beijing, China
Funder
Research Impact Fund
Hong Kong Environmental and Conservation Fund
Hong KongITC Innovation and Technology Fund Midstream Research Programme for Universities Project
Kuaishou
APRC - CityU New Research Initiatives
CityU - HKIDS Early Career Research Grant
SIRG - CityU Strategic Interdisciplinary Research Grant
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3657829
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2. M Mehdi Afsar, Trafford Crump, and Behrouz Far. 2021. Reinforcement learning based recommender systems: A survey. ACM Computing Surveys (CSUR) (2021).
3. Shalabh Bhatnagar, Mohammad Ghavamzadeh, Mark Lee, and Richard S Sutton. 2007. Incremental natural actor-critic algorithms. Advances in neural information processing systems 20 (2007).
4. Reinforcing User Retention in a Billion Scale Short Video Recommender System
5. Two-Stage Constrained Actor-Critic for Short Video Recommendation
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