DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling
arXiv:2509.03472v2 Announce Type: replace
Abstract: Differentially-Private SGD (DP-SGD) and its adaptive variant DP-Adam are powerful techniques to protect user privacy when using sensitive data to train neural networks. During training, converting mo…