A DRL-based per-class data subset selection with post-federation fine-tuning is claimed to improve personalized federated learning, but the experiments and the theoretical bound do not substantiate the claim.
Feddc: Federated learning with non-iid data via local drift decoupling and correction,
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Optimized Local Updates in Federated Learning via Reinforcement Learning
A DRL-based per-class data subset selection with post-federation fine-tuning is claimed to improve personalized federated learning, but the experiments and the theoretical bound do not substantiate the claim.