A VoL/TLW-based PDQN scheduler for NOMA federated meta-learning outperforms DDPG, OMA, equal-weight, and random baselines in simulation.
Federate d learning and meta learning: Approaches, applications, and directio ns,
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Optimizing Value of Learning in Task-Oriented Federated Meta-Learning Systems
A VoL/TLW-based PDQN scheduler for NOMA federated meta-learning outperforms DDPG, OMA, equal-weight, and random baselines in simulation.