1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2019★ 1 cited
PD-ML-Lite: Private Distributed Machine Learning from Lighweight Cryptography
Maksim Tsikhanovich, Malik Magdon-Ismail, Muhammad Ishaq +1
Privacy is a major issue in learning from distributed data. Recently the cryptographic literature has provided several tools for this task. However, these tools either reduce the q…
cs.CR2018
How Private Are Commonly-Used Voting Rules?
Ao Liu, Yun Lu, Lirong Xia +1
Differential privacy has been widely applied to provide privacy guarantees by adding random noise to the function output. However, it inevitably fails in many high-stakes voting sc…