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Found 2 papers, 2 papers with code
Decentralized Personalized Federated Learning based on a Conditional Sparse-to-Sparser Scheme
We provide a theoretical analysis of DA-DPFL's convergence by solidifying its applicability in decentralized and personalized learning.
FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization
Federated Learning (FL) has been successfully adopted for distributed training and inference of large-scale Deep Neural Networks (DNNs).
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