Task Assignment with Efficient Federated Preference Learning in Spatial Crowdsourcing-Reference-Cited by-同舟云学术

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Task Assignment with Efficient Federated Preference Learning in Spatial Crowdsourcing

Published:2023 Issue: Volume: Page:1-15
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Miao Hao¹^ORCID,Zhong Xiaolong²,Liu Jiaxin²,Zhao Yan¹^ORCID,Zhao Xiangyu³^ORCID,Qian Weizhu¹,Zheng Kai²^ORCID,Jensen Christian S.¹^ORCID

Affiliation:

1. department of Computer Science, Aalborg University, Aalborg, Denmark

2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

3. School of Data Science, City University of Hong Kong, Hong Kong, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/4358933/10239279.pdf?arnumber=10239279

Cited by 2 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. FRAMU: Attention-Based Machine Unlearning Using Federated Reinforcement Learning;IEEE Transactions on Knowledge and Data Engineering;2024-10

2. Spatial-Temporal Large Language Model for Traffic Prediction;2024 25th IEEE International Conference on Mobile Data Management (MDM);2024-06-24

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