SParSeFuL combines proximity-based self-federated learning with sparsification and quantization, but the paper is a proposal with no end-to-end evaluation.
Decentralized learning works: An empirical comparison of gossip learning and federated learning,
1 Pith paper cite this work, alongside 151 external citations. Polarity classification is still indexing.
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Sparse Self-Federated Learning for Energy Efficient Cooperative Intelligence in Society 5.0
SParSeFuL combines proximity-based self-federated learning with sparsification and quantization, but the paper is a proposal with no end-to-end evaluation.