Automated discovery of trade-off between utility, privacy and fairness in machine learning models
Authors: Bogdan Ficiu, Neil D. Lawrence, Andrei Paleyes | Published: 2023-11-27
トレードオフ分析
Does Differential Privacy Prevent Backdoor Attacks in Practice?
Authors: Fereshteh Razmi, Jian Lou, Li Xiong | Published: 2023-11-10
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Authors: Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen | Published: 2023-09-28 | Updated: 2024-03-18
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense
Authors: Yue Cui, Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu | Published: 2023-04-11
RareGAN: Generating Samples for Rare Classes
Authors: Zinan Lin, Hao Liang, Giulia Fanti, Vyas Sekar | Published: 2022-03-20
On Robust Prefix-Tuning for Text Classification
Authors: Zonghan Yang, Yang Liu | Published: 2022-03-19
Differentially Private Label Protection in Split Learning
Authors: Xin Yang, Jiankai Sun, Yuanshun Yao, Junyuan Xie, Chong Wang | Published: 2022-03-04
Label Leakage and Protection from Forward Embedding in Vertical Federated Learning
Authors: Jiankai Sun, Xin Yang, Yuanshun Yao, Chong Wang | Published: 2022-03-02 | Updated: 2022-05-25
PUMA: Performance Unchanged Model Augmentation for Training Data Removal
Authors: Ga Wu, Masoud Hashemi, Christopher Srinivasa | Published: 2022-03-02
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