4 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
PrivCode++: Latent-Conditioned Differentially Private Code Generation for Comprehensive Guarantees
Zheng Liu, Chen Gong, Terry Yue Zhuo +6
Large language models fine-tuned on instruction-code pairs may memorize and subsequently leak sensitive training data. Existing differentially private (DP) code generation methods…
HeteroFedSyn: Differentially Private Tabular Data Synthesis for Heterogeneous Federated Settings
Xiaochen Li, Fengyu Gao, Xizixiang Wei +3
Traditional Differential Privacy (DP) mechanisms are typically tailored to specific analysis tasks, which limits the reusability of protected data. DP tabular data synthesis overco…
Benchmarking Differentially Private Tabular Data Synthesis
Kai Chen, Xiaochen Li, Chen Gong +2
Differentially private (DP) tabular data synthesis generates artificial data that preserves the statistical properties of private data while safeguarding individual privacy. The em…
From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesis
Kecen Li, Chen Gong, Xiaochen Li +3
Differentially private (DP) image synthesis aims to generate synthetic images from a sensitive dataset, alleviating the privacy leakage concerns of organizations sharing and utiliz…