2 papers
cs.LG2026
Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping
Linzh Zhao, Aki Rehn, Mikko A. Heikkilä +2
Differential privacy (DP) has become an essential framework for privacy-preserving machine learning. Existing DP learning methods, however, often have disparate impacts on model pr…
cs.LG2026
On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
Aki Rehn, Linzh Zhao, Mikko A. Heikkilä +1
Differentially private (DP) transfer learning, i.e., fine-tuning a pretrained model on private data, is the current state-of-the-art approach for training large models under privac…