XZ
Xiaojiang Zuo
3 records found
1
Loci
Federated Continual Learning of Heterogeneous Tasks at Edge
Federated continual learning (FCL) has attracted growing attention in achieving collaborative model training among edge clients, each of which learns its local model for a sequence of tasks. Most existing FCL approaches aggregate clients' latest local models to exchange knowledge
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Edge applications are increasingly empowered by deep neural networks (DNN) and face the challenges of adapting or retraining models for the changes in input data domains and learning tasks. The existing techniques to enable DNN retraining on edge devices are to configure the memo
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RobustDA
Lightweight Robust Domain Adaptation for Evolving Data at Edge
AI applications powered by deep learning models are increasingly run natively at edge. A deployed model not only encounters continuously evolving input distributions (domains) but also faces adversarial attacks from third-party. This necessitates adapting the model to shifting do
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