The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection
Authors: Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, Om Thakkar | Published: 2021-11-09
プライバシーリスク管理
Distribution-Invariant Differential Privacy
Authors: Xuan Bi, Xiaotong Shen | Published: 2021-11-08 | Updated: 2022-06-06
Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence
Authors: Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis | Published: 2021-11-01 | Updated: 2021-11-29
Two-Bit Aggregation for Communication Efficient and Differentially Private Federated Learning
Authors: Mohammad Aghapour, Aidin Ferdowsi, Walid Saad | Published: 2021-10-06
Task-aware Privacy Preservation for Multi-dimensional Data
Authors: Jiangnan Cheng, Ao Tang, Sandeep Chinchali | Published: 2021-10-05 | Updated: 2022-08-08
Label differential privacy via clustering
Authors: Hossein Esfandiari, Vahab Mirrokni, Umar Syed, Sergei Vassilvitskii | Published: 2021-10-05
SecFL: Confidential Federated Learning using TEEs
Authors: Do Le Quoc, Christof Fetzer | Published: 2021-10-03 | Updated: 2021-10-07
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message
Authors: Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh, Amer Sinha | Published: 2021-09-27
MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers
Authors: Antoine Boutet, Thomas Lebrun, Jan Aalmoes, Adrien Baud | Published: 2021-09-26
A Validated Privacy-Utility Preserving Recommendation System with Local Differential Privacy
Authors: Seryne Rahali, Maryline Laurent, Souha Masmoudi, Charles Roux, Brice Mazeau | Published: 2021-09-23