On the accuracy and efficiency of group-wise clipping in differentially
private optimization

On the accuracy and efficiency of group-wise clipping in differentially private optimization

30 October 2023

Sheng Zha

George Karypis

Papers citing "On the accuracy and efficiency of group-wise clipping in differentially private optimization"

7 / 7 papers shown

Title
Towards hyperparameter-free optimization with differential privacy Zhiqi Bu Ruixuan Liu 24 1 0 02 Mar 2025
Tokens for Learning, Tokens for Unlearning: Mitigating Membership Inference Attacks in Large Language Models via Dual-Purpose Training Toan Tran Ruixuan Liu Li Xiong MU 41 0 0 27 Feb 2025
LLM-PBE: Assessing Data Privacy in Large Language Models Qinbin Li Junyuan Hong Chulin Xie Jeffrey Tan Rachel Xin ... Dan Hendrycks Zhangyang Wang Bo Li Bingsheng He Dawn Song ELM PILM 36 12 0 23 Aug 2024
Pre-training Differentially Private Models with Limited Public Data Zhiqi Bu Xinwei Zhang Mingyi Hong Sheng Zha George Karypis 77 3 0 28 Feb 2024
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu J. Mao Shiyun Xu 131 47 0 21 May 2022
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 134 344 0 13 Oct 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 144 348 0 25 Sep 2021