Generative Learning Plan Recommendation for Employees: A Performance-aware Reinforcement Learning Approach

Author:

Zheng Zhi1ORCID,Sun Ying2ORCID,Song Xin3ORCID,Zhu Hengshu4ORCID,Xiong Hui5ORCID

Affiliation:

1. School of Data Science, University of Science and Technology of China, China

2. Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), China

3. Baidu Talent Intelligence Center, Baidu Inc., China

4. Career Science Lab, BOSS Zhipin, China

5. Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), China and The Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong

Publisher

ACM

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. MIRROR: A Multi-View Reciprocal Recommender System for Online Recruitment;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

3. Generative Künstliche Intelligenz in Unterricht und Unterrichtsforschung – Chancen und Herausforderungen;Unterrichtswissenschaft;2024-06

4. Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning;Proceedings of the ACM Web Conference 2024;2024-05-13

5. Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation;Proceedings of the 17th ACM International Conference on Web Search and Data Mining;2024-03-04

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