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May, 2024
无需演练的联邦领域增量学习
Rehearsal-free Federated Domain-incremental Learning
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Rui Sun, Haoran Duan, Jiahua Dong, Varun Ojha, Tejal Shah...
TL;DR
我们引入了一种无需复习的联邦域增量学习框架RefFiL,基于全局提示共享范式,以缓解联邦域增量学习中的灾难性遗忘挑战,不需要额外的内存空间,适用于隐私敏感和资源受限设备。
Abstract
We introduce a
rehearsal-free federated domain incremental learning
framework,
reffil
, based on a global prompt-sharing paradigm to alleviate
cat
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