A two-stage FL aggregation method with proxy models for heterogeneous LEO networks extends contact windows and achieves 86.59-90.57% accuracy with 1.5-2.2x faster convergence than baselines.
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Topology-Aware Two-Stage Federated Learning via Proxy Models for Sub-THz Heterogeneous LEO Communications
A two-stage FL aggregation method with proxy models for heterogeneous LEO networks extends contact windows and achieves 86.59-90.57% accuracy with 1.5-2.2x faster convergence than baselines.