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DART-FL: Burst-Aware Multitask Federated Learning under Dynamic Inference Demand at the Edge
Edge intelligence systems increasingly require model training and online inference to coexist on resource-constrained devices, while inference demand can vary substantially across tasks over time. This creates two coupled challenges: sufficient computation must be reserved for inference to maintain
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