Name
Title | ||
|---|---|---|
Blockchain Empowered Reliable Federated Learning by Worker Selection: A Trustworthy Reputation Evaluation Method |
Abstract | ||
|---|---|---|
Federated learning is a distributed machine learning framework that enables distributed model training with local datasets, which can effectively protect the data privacy of workers (i.e., intelligent edge nodes). The majority of federated learning algorithms assume that the workers are trusted and voluntarily participate in the cooperative model training process. However, the situation in practic... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/WCNCW49093.2021.9420026 | 2021 IEEE Wireless Communications and Networking Conference Workshops (WCNCW) |
Keywords | DocType | ISSN |
Training,Data privacy,Analytical models,Conferences,Blockchain,Machine learning,Predictive models | Conference | 2167-8189 |
ISBN | Citations | PageRank |
978-1-7281-9507-0 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qinnan Zhang | 1 | 0 | 0.34 |
| Qingyang Ding | 2 | 0 | 0.34 |
| Jianming Zhu | 3 | 2 | 2.42 |
| Dandan Li | 4 | 27 | 7.99 |