A closed-form Nash equilibrium and Stackelberg search show how an SFL owner should set incentives and cut layer to elicit client data contributions.
Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.GT 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?
A closed-form Nash equilibrium and Stackelberg search show how an SFL owner should set incentives and cut layer to elicit client data contributions.