OAK

Reward-based participant selection for improving federated reinforcement learning

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Type
Article
Author(s)
이웅희
Department
AI응용학과
Creator
이웅희
Alternative Author(s)
Woonghee Lee
Citation Title
ICT Express
Citation Volume
5
Citation Number
9
Citation Start Page
803
Issued Date
2023-10
DOI
10.1016/j.icte.2022.08.008
EISSN
2405-9595
Publisher
Korean Institute of Communications and Information Sciences(한국통신학회)
Keyword
Federated learningReinforcement learningFederated reinforcement learningParticipant selection
URI
http://dspace.hansung.ac.kr/handle/2024.oak/1794
Appears in Collections:
AI응용학과 > 1. Journal Articles
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