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cs.LG2023
Concept Matching: Clustering-based Federated Continual Learning
Xiaopeng Jiang, Cristian Borcea
Federated Continual Learning (FCL) has emerged as a promising paradigm that combines Federated Learning (FL) and Continual Learning (CL). To achieve good model accuracy, FCL needs…
cs.LG2023
Zone-based Federated Learning for Mobile Sensing Data
Xiaopeng Jiang, Thinh On, NhatHai Phan +5
Mobile apps, such as mHealth and wellness applications, can benefit from deep learning (DL) models trained with mobile sensing data collected by smart phones or wearable devices. H…
cs.LG2023★ 2 cited
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning
Xiaopeng Jiang, Cristian Borcea
Federated Learning (FL) is a privacy-preserving distributed deep learning paradigm that involves substantial communication and computation effort, which is a problem for resource-c…