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Found 3 papers, 1 papers with code
FedCME: Client Matching and Classifier Exchanging to Handle Data Heterogeneity in Federated Learning
This can alleviate the performance degradation on the aggregated global model.
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
To achieve model personalization while maintaining generalization, in this paper, we propose a new approach, named PFL-MoE, which mixes outputs of the personalized model and global model via the MoE architecture.
Boros: Secure Cross-Channel Transfers via Channel Hub
In this paper, we design and develop a novel off-chain system to shorten the routing path for the payment network.
Cryptography and Security
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