18 citations · 18 across the 2 of their papers we have counts for
2 papers
cs.CR2022★ 18 cited
A Differentially Private Framework for Deep Learning with Convexified Loss Functions
Zhigang Lu, Hassan Jameel Asghar, Mohamed Ali Kaafar +2
Differential privacy (DP) has been applied in deep learning for preserving privacy of the underlying training sets. Existing DP practice falls into three categories - objective per…
cs.LG2021
On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models
Benjamin Zi Hao Zhao, Aviral Agrawal, Catisha Coburn +5
With an increase in low-cost machine learning APIs, advanced machine learning models may be trained on private datasets and monetized by providing them as a service. However, priva…