Abstract: Federated learning (FL) allows multiple clients to collaboratively learn a globally shared model through cycles of model aggregation and local model training, without the need to share data.
Abstract: Bayesian optimization (BO), a data-efficient method for expensive black-box optimization, has traditionally focused on single-task scenarios, ignoring potential correlations among related ...
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