Name
Title | ||
|---|---|---|
P3GM: Private High-Dimensional Data Release via Privacy Preserving Phased Generative Model |
Abstract | ||
|---|---|---|
How can we release a massive volume of sensitive data while mitigating privacy risks? Privacy-preserving data synthesis enables the data holder to outsource analytical tasks to an untrusted third party. The state-of-the-art approach for this problem is to build a generative model under differential privacy, which offers a rigorous privacy guarantee. However, the existing method cannot adequately h... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICDE51399.2021.00022 | 2021 IEEE 37th International Conference on Data Engineering (ICDE) |
Keywords | DocType | ISSN |
differential privacy,variational autoencoder,generative model,privacy preserving data synthesis | Conference | 1084-4627 |
ISBN | Citations | PageRank |
978-1-7281-9184-3 | 1 | 0.35 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takagi Shun | 1 | 1 | 0.69 |
| Tsubasa Takahashi | 2 | 1 | 1.03 |
| Yang Cao | 3 | 34 | 12.55 |
| Masatoshi Yoshikawa | 4 | 1655 | 282.19 |