DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM
Authors: Bao Wang, Quanquan Gu, March Boedihardjo, Farzin Barekat, Stanley J. Osher | Published: 2019-06-28 | Updated: 2019-12-07
Privacy Protection
Secure Summation via Subset Sums: A New Primitive for Privacy-Preserving Distributed Machine Learning
Authors: Valentin Hartmann, Robert West | Published: 2019-06-27 | Updated: 2023-06-19
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
Authors: Klas Leino, Matt Fredrikson | Published: 2019-06-27 | Updated: 2020-06-24
The Cost of a Reductions Approach to Private Fair Optimization
Authors: Daniel Alabi | Published: 2019-06-23 | Updated: 2021-05-23
Deep Leakage from Gradients
Authors: Ligeng Zhu, Zhijian Liu, Song Han | Published: 2019-06-21 | Updated: 2019-12-19
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
Authors: Badih Ghazi, Rasmus Pagh, Ameya Velingker | Published: 2019-06-19 | Updated: 2019-12-02
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation
Authors: Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon | Published: 2019-06-19 | Updated: 2020-10-25
Membership Privacy for Machine Learning Models Through Knowledge Transfer
Authors: Virat Shejwalkar, Amir Houmansadr | Published: 2019-06-15 | Updated: 2020-12-31
Real-Time Privacy-Preserving Data Release for Smart Meters
Authors: Mohammadhadi Shateri, Francisco Messina, Pablo Piantanida, Fabrice Labeau | Published: 2019-06-14 | Updated: 2021-11-25
Computing Tight Differential Privacy Guarantees Using FFT
Authors: Antti Koskela, Joonas Jälkö, Antti Honkela | Published: 2019-06-07 | Updated: 2019-11-04