Name
Title | ||
|---|---|---|
Just Keep Your Concerns Private: Guaranteeing Heterogeneous Privacy and Achieving High Availability for ERM Algorithms |
Abstract | ||
|---|---|---|
Traditional implementations of differential privacy implicitly assume that users have homogeneous privacy requirement for all attributes of data. They provide a uniform level of privacy guarantee for all attributes by using a single privacy budget, $\varepsilon$. However, this brings trouble to users in practice applications, where privacy requirements are often heterogeneous. In this c... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TrustCom53373.2021.00064 | 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) |
Keywords | DocType | ISBN |
Privacy,Differential privacy,Adaptation models,Machine learning algorithms,Conferences,Training data,Security | Conference | 978-1-6654-1658-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||