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[IPMI'2025]Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning

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Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning

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In this work, we take the first step to propose a novel server-side FCL pattern in medical domain, Dynamic Allocation Hypernetwork with adaptive model recalibration (FedDAH). It is to facilitate collaborative learning under the distinct and dynamic task streams across clients. To alleviate the catastrophic forgetting,

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[IPMI'2025]Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning

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