Anvith Thudi

Differentially Private Mixing of Public Datasets Improves Private Learning

Many machine learning applications involve sensitive data and therefore require training under differential privacy (DP). However, DP training often degrades model utility. In some cases, first pre-training the model on"public"data before finetuning with DP on the sensitive data can reduce the drop in utility. However,...