Closed-Form Bounds for DP-SGD against Record-level Inference
Authors: Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin | Published: 2024-02-22
プライバシー保護手法
Revisiting Differentially Private Hyper-parameter Tuning
Authors: Zihang Xiang, Tianhao Wang, Chenglong Wang, Di Wang | Published: 2024-02-20 | Updated: 2024-06-04
Bounding Reconstruction Attack Success of Adversaries Without Data Priors
Authors: Alexander Ziller, Anneliese Riess, Kristian Schwethelm, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis | Published: 2024-02-20
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
Authors: Songjie Xie, Youlong Wu, Jiaxuan Li, Ming Ding, Khaled B. Letaief | Published: 2024-02-16
A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets
Authors: Irina Arévalo, Jose L. Salmeron | Published: 2024-02-15
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service
Authors: Yu Liu, Zibo Wang, Yifei Zhu, Chen Chen | Published: 2024-02-15
Why Does Differential Privacy with Large Epsilon Defend Against Practical Membership Inference Attacks?
Authors: Andrew Lowy, Zhuohang Li, Jing Liu, Toshiaki Koike-Akino, Kieran Parsons, Ye Wang | Published: 2024-02-14
Auditing Private Prediction
Authors: Karan Chadha, Matthew Jagielski, Nicolas Papernot, Christopher Choquette-Choo, Milad Nasr | Published: 2024-02-14
I can’t see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption
Authors: Prajwal Panzade, Daniel Takabi, Zhipeng Cai | Published: 2024-02-14
Differentially Private Training of Mixture of Experts Models
Authors: Pierre Tholoniat, Huseyin A. Inan, Janardhan Kulkarni, Robert Sim | Published: 2024-02-11