DFRD: data-free robustness distillation for heterogeneous federated learning

K Luo, S Wang, Y Fu, X Li, Y Lan, M Gao - arXiv preprint arXiv:2309.13546, 2023 - arxiv.org
Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm
in which clients enable collaborative training without compromising private data. However …
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DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning

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DFRD: data-free robustness distillation for heterogeneous federated learning

K Luo, S Wang, Y Fu, X Li, Y Lan, M Gao - Proceedings of the 37th …, 2023 - dl.acm.org
Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm
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DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning

K Luo, S Wang, Y Fu, X Li, Y Lan, M Gao - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm
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[PDF] neurips.cc

[PDF][PDF] DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning

K Luo, S Wang, Y Fu, X Li, Y Lan, M Gao - papers.neurips.cc
Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm
in which clients enable collaborative training without compromising private data. However …