3 papers
cs.LG2024
Enhancing DP-SGD through Non-monotonous Adaptive Scaling Gradient Weight
Tao Huang, Qingyu Huang, Xin Shi +4
In the domain of deep learning, the challenge of protecting sensitive data while maintaining model utility is significant. Traditional Differential Privacy (DP) techniques such as…
cs.CV2024
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising
Tao Huang, Jiayang Meng, Hong Chen +4
We investigate the construction of gradient-guided conditional diffusion models for reconstructing private images, focusing on the adversarial interplay between differential privac…
cs.LG2024
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios
Tao Huang, Ziyang Chen, Jiayang Meng +4
In the context of machine unlearning, the primary challenge lies in effectively removing traces of private data from trained models while maintaining model performance and security…