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FedImp: Enhancing Federated Learning Convergence with Impurity-Based Weighting

arXiv cs.LG · 2026-08-18 Cached

FedImp is a novel federated learning algorithm that uses impurity-based weighting to enhance convergence speed in non-IID data settings, showing significant reductions in communication rounds compared to baselines.

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