Name
Abstract | ||
|---|---|---|
Deep learning has become a key technology on modeling large amounts of multi-sourced data. For privacy concerns, the data sharing among companies and organizations is increasingly difficult. In this paper, we present a crowd-sourced federated learning solution to train neural networks with a hybrid blockchain architecture. Smart contracts are used to share data authentications on the main chain, w... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISCC53001.2021.9631423 | 2021 IEEE Symposium on Computers and Communications (ISCC) |
Keywords | DocType | ISBN |
Deep learning,Computers,Data privacy,Smart contracts,Neural networks,Collaborative work,Data models | Conference | 978-1-6654-2744-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shili Hu | 1 | 0 | 1.69 |
| Jiangfeng Li | 2 | 7 | 3.50 |
| Qinpei Zhao | 3 | 132 | 17.11 |
| Chenxi Zhang | 4 | 24 | 10.25 |
| Zhang Zijian | 5 | 57 | 10.32 |
| Yang Shi | 6 | 18 | 4.36 |