Pengju Wang

Model Conversion via Differentially Private Data-Free Distillation

2023 · arXiv (Cornell University)

While massive valuable deep models trained on large-scale data have been released to facilitate the artificial intelligence community, they may encounter attacks in deployment which leads to privacy leakage of training data. In this work, …

Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation

2024 · arXiv (Cornell University)

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 deployment. In this paper, we present an effective …