Name
Abstract | ||
|---|---|---|
Crowdsensing has emerged as a powerful tool to collect IoT big data. Moving big data to the cloud for analysis is time consuming and has the risk of data privacy leakage. An alternative is to leave the training data distributed on mobile devices, and learn a shared model by aggregating locally computed updates. In this article, we propose a CrowdLearning system, which employs MUs for big data coll... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/MNET.001.1900286 | IEEE Network |
Keywords | DocType | Volume |
Training,Big Data,Machine learning,Mobile handsets,Sensors,Computational modeling,Task analysis | Journal | 34 |
Issue | ISSN | Citations |
3 | 0890-8044 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yufeng Zhan | 1 | 1 | 0.35 |
| Peng Li | 2 | 196 | 24.77 |
| Kun Wang | 3 | 364 | 30.23 |
| Song Guo | 4 | 3431 | 278.71 |
| Yuanqing Xia | 5 | 3132 | 232.57 |