Optimal Unbiased Randomizers for Regression with Label Differential Privacy

9 December 2023

Papers citing "Optimal Unbiased Randomizers for Regression with Label Differential Privacy"

8 / 8 papers shown

Title
Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das Inderjit S Dhillon Alessandro Epasto Adel Javanmard Jieming Mao Vahab Mirrokni Sujay Sanghavi Peilin Zhong 44 1 0 17 Jun 2024
Enhancing Learning with Label Differential Privacy by Vector Approximation Puning Zhao Rongfei Fan Huiwen Wu Qingming Li Jiafei Wu Zhe Liu 23 1 0 24 May 2024
Locally Private Estimation with Public Features Yuheng Ma Ke Jia Hanfang Yang 34 3 0 22 May 2024
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 346 0 13 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 123 119 0 07 Oct 2021
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 55 36 0 27 Sep 2021
Label Leakage and Protection in Two-party Split Learning Oscar Li Jiankai Sun Xin Yang Weihao Gao Hongyi Zhang Junyuan Xie Virginia Smith Chong-Jun Wang FedML 122 139 0 17 Feb 2021
The Optimal Mechanism in Differential Privacy: Multidimensional Setting Quan Geng Pramod Viswanath 79 122 0 02 Dec 2013