The paper proposes a peer-to-peer federated learning framework with validation-loss-based model sharing and a weighted loss-correction term, but the correction term has zero gradient and the experiments show implausible identical results for two different architectures.
The global burden of pathogens and pests on major food crops,
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Loss-Guided Model Sharing and Local Learning Correction in Decentralized Federated Learning for Crop Disease Classification
The paper proposes a peer-to-peer federated learning framework with validation-loss-based model sharing and a weighted loss-correction term, but the correction term has zero gradient and the experiments show implausible identical results for two different architectures.