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When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile
  Crowdsensing System

When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System

20 February 2021
Bowen Zhao
Ximeng Liu
Wei Chen
    FedML
ArXivPDFHTML

Papers citing "When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System"

4 / 4 papers shown
Title
Ten Challenging Problems in Federated Foundation Models
Ten Challenging Problems in Federated Foundation Models
Tao Fan
Hanlin Gu
Xuemei Cao
Chee Seng Chan
Qian Chen
...
Yuanyuan Zhang
Xiaojin Zhang
Zhenzhe Zheng
Lixin Fan
Qiang Yang
FedML
89
4
0
14 Feb 2025
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and
  Insights
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights
Maryam Ben Driss
Essaid Sabir
H. Elbiaze
Walid Saad
41
7
0
07 Dec 2023
Incentive Mechanisms for Federated Learning: From Economic and Game
  Theoretic Perspective
Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective
Xuezhen Tu
Kun Zhu
Nguyen Cong Luong
Dusit Niyato
Yang Zhang
Juan Li
FedML
AI4CE
43
119
0
20 Nov 2021
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation
  in Federated Learning
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning
Zelei Liu
Yuanyuan Chen
Han Yu
Yang Liu
Li-zhen Cui
FedML
TDI
27
124
0
05 Sep 2021
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