← Optimization & Theory
Machine Learning › Optimization & Theory ›

Privacy

7 directly classified papers

Papers per year

Papers

Enhancing DPSGD via Per-Sample Momentum and Low-Pass Filtering AAAI 2026
The Role of Over-Parameterization in Machine Learning – the Good, the Bad, the Ugly AAAI 2024
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification NIPS 2024
Differentially Private Generalized Linear Models Revisited NIPS 2022
Momentum Aggregation for Private Non-convex ERM NIPS 2022
On the Intrinsic Differential Privacy of Bagging IJCAI 2021
Private Center Points and Learning of Halfspaces COLT 2019