DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning

2 November 2023

Papers citing "DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning"

6 / 6 papers shown

Title
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models Haoteng Yin Rongzhe Wei Eli Chien P. Li 28 0 0 10 Oct 2024
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang Zhiqi Bu Borja Balle Mingyi Hong Meisam Razaviyayn Vahab Mirrokni 74 2 0 04 Oct 2024
Optimal Layer Selection for Latent Data Augmentation Tomoumi Takase Ryo Karakida 28 1 0 24 Aug 2024
Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-perfect Representation Learning Chendi Wang Yuqing Zhu Weijie J. Su Yu-Xiang Wang AAML 50 4 0 14 May 2024
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 94 167 0 01 Mar 2023
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu J. Mao Shiyun Xu 131 47 0 21 May 2022