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cs.LG2024
Federated Learning with Label-Masking Distillation
Jianghu Lu, Shikun Li, Kexin Bao +3
Federated learning provides a privacy-preserving manner to collaboratively train models on data distributed over multiple local clients via the coordination of a global server. In…
cs.LG2024
Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation
Bochao Liu, Jianghu Lu, Pengju Wang +4
Deep learning models can achieve high inference accuracy by extracting rich knowledge from massive well-annotated data, but may pose the risk of data privacy leakage in practical d…