Naturally Private Recommendations with Determinantal Point Processes
Authors: Jack Fitzsimons, Agustín Freitas Pasqualini, Robert Pisarczyk, Dmitrii Usynin | Published: 2024-05-22
Privacy Protection Method
Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent
Authors: Holger Dette, Carina Graw | Published: 2024-05-21
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
Authors: Tianqu Kang, Lumin Liu, Hengtao He, Jun Zhang, S. H. Song, Khaled B. Letaief | Published: 2024-05-16
Learnable Privacy Neurons Localization in Language Models
Authors: Ruizhe Chen, Tianxiang Hu, Yang Feng, Zuozhu Liu | Published: 2024-05-16
Differentially Private Federated Learning: A Systematic Review
Authors: Jie Fu, Yuan Hong, Xinpeng Ling, Leixia Wang, Xun Ran, Zhiyu Sun, Wendy Hui Wang, Zhili Chen, Yang Cao | Published: 2024-05-14 | Updated: 2024-05-20
Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems
Authors: Amin Aminifar, Matin Shokri, Amir Aminifar | Published: 2024-05-09 | Updated: 2024-09-13
Model Inversion Robustness: Can Transfer Learning Help?
Authors: Sy-Tuyen Ho, Koh Jun Hao, Keshigeyan Chandrasegaran, Ngoc-Bao Nguyen, Ngai-Man Cheung | Published: 2024-05-09
Differentially Private Post-Processing for Fair Regression
Authors: Ruicheng Xian, Qiaobo Li, Gautam Kamath, Han Zhao | Published: 2024-05-07
Locally Differentially Private In-Context Learning
Authors: Chunyan Zheng, Keke Sun, Wenhao Zhao, Haibo Zhou, Lixin Jiang, Shaoyang Song, Chunlai Zhou | Published: 2024-05-07 | Updated: 2024-05-08
IPFed: Identity protected federated learning for user authentication
Authors: Yosuke Kaga, Yusei Suzuki, Kenta Takahashi | Published: 2024-05-07