Federated Learning For Robots
Federated Learning for Robots is a distributed machine learning framework in which multiple robotic agents collaboratively train a shared global model while preserving data locality by exchanging model updates rather than raw sensory data.
8
Publications
1K
Citations
32
Authors
17
Institutions
Publications per year
2017–2026
8
Parents
8
Federated Learning in Robotic and Autonomous Systems
Xianjia Yu, Jorge Peña Queralta, Jukka Heikkonen et al. · Procedia Computer Science · 2021 · 70 citations · Full text
Robot target recognition using deep federated learning
Bin Xue, Yi He, Jing Feng et al. · International Journal of Intelligent Systems · 2021 · 51 citations
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17

University of Turku
Turku, Finland
2 h-index
7 publications
343 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
1 h-index
1 publications
87 citations

National Defense University
Washington, United States
1 h-index
4 publications
204 citations
University of Southern California
Los Angeles, United States
1 h-index
1 publications
16 citations
Shenzhen Institutes of Advanced Technology
Shenzhen, China
1 h-index
2 publications
174 citations

University of Colorado Denver
Denver, United States
1 h-index
1 publications
16 citations

Xi'an Jiaotong University
Xi'an, China
1 h-index
1 publications
51 citations
University of Chinese Academy of Sciences
Beijing, China
1 h-index
1 publications
87 citations
1–8 of 17
2 publications · 91 citations
2
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1 publications · 51 citations
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1 publications · 722 citations
1
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1 publications · 87 citations
1
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1 publications · 24 citations
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