Federated Learning Incentive Mechanism Design via Shapley Value and Pareto Optimality
Federated learning (FL) is a distributed machine learning framework that can effectively help multiple players to use data to train federated models while complying with their privacy, data security, and government regulations. Due to federated model training, an accurate model should be trained, an...
Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-06-01
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Series: | Axioms |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-1680/12/7/636 |