LIGHTYEAR selects each client's aggregation set by scoring how similarly models behave on private validation data with a neural tangent kernel, improving robustness to heterogeneous and malfunctioning clients in peer-to-peer federated learning.
Benchmarking robustness and privacy- preserving methods in federated learning.Future Generation Computer Systems, 155: 18–38, 2024
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Beyond Parameter Space: NTK-Guided Personalized Aggregation for Robust Federated Learning
LIGHTYEAR selects each client's aggregation set by scoring how similarly models behave on private validation data with a neural tangent kernel, improving robustness to heterogeneous and malfunctioning clients in peer-to-peer federated learning.