LeaDQ uses QMIX-based multi-agent reinforcement learning to learn per-client policies for selecting which streaming unlabeled samples to query labels for in federated learning, achieving higher global model accuracy than several baselines.
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Learn How to Query from Unlabeled Data Streams in Federated Learning
LeaDQ uses QMIX-based multi-agent reinforcement learning to learn per-client policies for selecting which streaming unlabeled samples to query labels for in federated learning, achieving higher global model accuracy than several baselines.