Efficient personalized federated learning via sparse model-adaptation

D Chen, L Yao, D Gao, B Ding… - … Conference on Machine …, 2023 - proceedings.mlr.press
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …
被引用次数：21 相关文章
[PDF] mlr.press

[PDF][PDF] Efficient Personalized Federated Learning via Sparse Model-Adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - proceedings.mlr.press
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …

Efficient Personalized Federated Learning via Sparse Model-Adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - openreview.net
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …

Efficient Personalized Federated Learning via Sparse Model-Adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …

Efficient Personalized Federated Learning via Sparse Model-Adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - arXiv preprint arXiv:2305.02776, 2023 - arxiv.org
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …

Efficient personalized federated learning via sparse model-adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - Proceedings of the 40th …, 2023 - dl.acm.org
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …
[PDF] github.io

[PDF][PDF] Efficient Personalized Federated Learning via Sparse Model-Adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - bolinding.github.io
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …

Efficient Personalized Federated Learning via Sparse Model-Adaptation

D Chen, L Yao, D Gao, B Ding, Y Li - openreview.net
Federated Learning (FL) aims to train machine learning models for multiple clients without
sharing their own private data. Due to the heterogeneity of clients' local data distribution …