Improving Differentially Private SGD via Randomly Sparsified Gradients
Authors: Junyi Zhu, Matthew B. Blaschko | Published: 2021-12-01 | Updated: 2023-06-28
Privacy Risk Management
Node-Level Differentially Private Graph Neural Networks
Authors: Ameya Daigavane, Gagan Madan, Aditya Sinha, Abhradeep Guha Thakurta, Gaurav Aggarwal, Prateek Jain | Published: 2021-11-23 | Updated: 2022-08-26
Flatee: Federated Learning Across Trusted Execution Environments
Authors: Arup Mondal, Yash More, Ruthu Hulikal Rooparaghunath, Debayan Gupta | Published: 2021-11-12
Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System
Authors: Timon Rückel, Johannes Sedlmeir, Peter Hofmann | Published: 2021-11-11
Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities
Authors: Esma Mansouri-Benssassi, Simon Rogers, Jim Smith, Felix Ritchie, Emily Jefferson | Published: 2021-11-10 | Updated: 2022-08-20
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
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