9 citations · 9 across the 1 of their papers we have counts for
3 papers
stat.ML2021★ 9 cited
Federated -Differential Privacy
Qinqing Zheng, Shuxiao Chen, Qi Long +1
Federated learning (FL) is a training paradigm where the clients collaboratively learn models by repeatedly sharing information without compromising much on the privacy of their lo…
stat.ML2020
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
Qinqing Zheng, Jinshuo Dong, Qi Long +1
Datasets containing sensitive information are often sequentially analyzed by many algorithms. This raises a fundamental question in differential privacy regarding how the overall p…
cs.LG2019
Deep Learning with Gaussian Differential Privacy
Zhiqi Bu, Jinshuo Dong, Qi Long +1
Deep learning models are often trained on datasets that contain sensitive information such as individuals' shopping transactions, personal contacts, and medical records. An increas…