Differentially Private Diffusion Models
Authors: Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis | Published: 2022-10-18 | Updated: 2023-12-31
Privacy Assessment
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling
Authors: Jianxin Wei, Ergute Bao, Xiaokui Xiao, Yin Yang | Published: 2022-10-18 | Updated: 2024-08-01
Stochastic Differentially Private and Fair Learning
Authors: Andrew Lowy, Devansh Gupta, Meisam Razaviyayn | Published: 2022-10-17 | Updated: 2023-06-03
A General Framework for Auditing Differentially Private Machine Learning
Authors: Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa | Published: 2022-10-16 | Updated: 2023-01-06
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct)
Authors: Hao Wang, Wanyu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang | Published: 2022-10-07
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints
Authors: Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Yarong Mu, Shuang Song, Om Thakkar, Abhradeep Thakurta, Xinyi Zheng | Published: 2022-10-04 | Updated: 2024-09-17
Certified Data Removal in Sum-Product Networks
Authors: Alexander Becker, Thomas Liebig | Published: 2022-10-04
No Free Lunch in “Privacy for Free: How does Dataset Condensation Help Privacy”
Authors: Nicholas Carlini, Vitaly Feldman, Milad Nasr | Published: 2022-09-29
Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy
Authors: Kai Packhäuser, Sebastian Gündel, Florian Thamm, Felix Denzinger, Andreas Maier | Published: 2022-09-23 | Updated: 2023-07-24
Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models
Authors: Sohaib Ahmad, Benjamin Fuller, Kaleel Mahmood | Published: 2022-09-22