2 papers
cs.LG2026
A Full-Pipeline Framework for Evaluating Membership Inference Attacks in Machine Learning
Ding Chen, Xinwen Cheng, Xuyang Zhong +3
While Membership Inference Attacks (MIAs) are the prevailing method for identifying training data, their application has expanded into privacy auditing and machine unlearning. Neve…
cs.LG2024
Differentially Private Neural Network Training Under the Hidden State Assumption
Ding Chen, Haochen Luo, Xiaofei Wang +1
Current differentially private learning paradigms face a severe utility bottleneck: DP-SGD degrades performance through noise accumulation over training steps, while aggregation-ba…