FedQuad uses quadruplet constraints and stochastic client selection in federated learning to reduce representation misalignment and improve generalization on heterogeneous data.
Tackling data heterogeneity in federated learning through knowledge distillation with inequitable aggregation
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Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis
FedQuad uses quadruplet constraints and stochastic client selection in federated learning to reduce representation misalignment and improve generalization on heterogeneous data.