Ke Li

FedBudget: A Budget-Aware Federated Learning Method for Communication-Constrained Distributed Data Mining

Sensitivity and convergence analyses confirm the robustness of the proposed scheduling mechanism and its stable communication–performance trade-off, indicating that explicit budget-aware participation modeling improves communication efficiency in federated data mining while preserving a simple and compatible training pipeline.