To cope with the impact of different device computing capabilities and non-independent uniformly distributed data on federated learning performance. and to efficiently schedule terminal devices to complete model aggregation. a method of node selection based on deep reinforcement learning was proposed. It considered training quality and efficiency of heterogeneous terminal devices. https://www.mariameetsanna.com/product-category/hydrating-curl-cream/
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