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cs.LG2025
An Improved Privacy and Utility Analysis of Differentially Private SGD with Bounded Domain and Smooth Losses
Hao Liang, Wanrong Zhang, Xinlei He +2
Differentially Private Stochastic Gradient Descent (DPSGD) is widely used to protect sensitive data during the training of machine learning models, but its privacy guarantee often…
cs.LG2021★ 6 cited
Quantifying and Mitigating Privacy Risks of Contrastive Learning
Xinlei He, Yang Zhang
Data is the key factor to drive the development of machine learning (ML) during the past decade. However, high-quality data, in particular labeled data, is often hard and expensive…