On the Privacy Risks of Model Explanations
Authors: Reza Shokri, Martin Strobel, Yair Zick | Published: 2019-06-29 | Updated: 2021-02-05
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
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
Adversarial Robustness via Label-Smoothing
Authors: Morgane Goibert, Elvis Dohmatob | Published: 2019-06-27 | Updated: 2019-10-15
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks
Authors: Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz | Published: 2019-06-26 | Updated: 2020-03-03
The Cost of a Reductions Approach to Private Fair Optimization
Authors: Daniel Alabi | Published: 2019-06-23 | Updated: 2021-05-23
Adversarial Examples to Fool Iris Recognition Systems
Authors: Sobhan Soleymani, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi | Published: 2019-06-21 | Updated: 2019-07-18
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