Spectral co-distillation for personalized federated learning

Z Chen, H Yang, T Quek… - Advances in Neural …, 2023 - proceedings.neurips.cc
Personalized federated learning (PFL) has been widely investigated to address the
challenge of data heterogeneity, especially when a single generic model is inadequate in …
被引用次数：5 相关文章

Spectral co-distillation for personalized federated learning

Z Chen, HH Yang, TQS Quek, KFE Chong - Proceedings of the 37th …, 2023 - dl.acm.org
Personalized federated learning (PFL) has been widely investigated to address the
challenge of data heterogeneity, especially when a single generic model is inadequate in …

Spectral Co-Distillation for Personalized Federated Learning

Z Chen, HH Yang, TQS Quek, KFE Chong - arXiv preprint arXiv …, 2024 - arxiv.org
Personalized federated learning (PFL) has been widely investigated to address the
challenge of data heterogeneity, especially when a single generic model is inadequate in …

Spectral Co-Distillation for Personalized Federated Learning

Z Chen, HH Yang, TQS Quek, KFE Chong - arXiv e-prints, 2024 - ui.adsabs.harvard.edu
Personalized federated learning (PFL) has been widely investigated to address the
challenge of data heterogeneity, especially when a single generic model is inadequate in …

Spectral Co-Distillation for Personalized Federated Learning

Z Chen, HH Yang, T Quek, KFE Chong - Thirty-seventh Conference on … - openreview.net
Personalized federated learning (PFL) has been widely investigated to address the
challenge of data heterogeneity, especially when a single generic model is inadequate in …

Spectral Co-Distillation for Personalized Federated Learning

Z Chen, HH Yang, TQS Quek… - Advances in Neural …, 2023 - researchoutput.ncku.edu.tw
Personalized federated learning (PFL) has been widely investigated to address the
challenge of data heterogeneity, especially when a single generic model is inadequate in …