2 papers
cs.LG2026
Privacy-Preserving Model Transcription with Differentially Private Synthetic Distillation
Bochao Liu, Shiming Ge, Pengju Wang +2
While many deep learning models trained on private datasets have been deployed in various practical tasks, they may pose a privacy leakage risk as attackers could recover informati…
cs.LG2024
Towards Personalized Federated Learning via Comprehensive Knowledge Distillation
Pengju Wang, Bochao Liu, Weijia Guo +2
Federated learning is a distributed machine learning paradigm designed to protect data privacy. However, data heterogeneity across various clients results in catastrophic forgettin…