Name
Title | ||
|---|---|---|
Federated Learning Method Based on Knowledge Distillation and Deep Gradient Compression |
Abstract | ||
|---|---|---|
Federated learning is a new type of multi-agency collaborative training model paradigm, which is widely used in many fields, among which communication overhead is a key issue. In order to reduce the amount of data transmitted in the communication process, we propose a federated learning algorithm based on knowledge distillation and deep gradient compression (Fed-KDDGC-SGD). First, we use local dat... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CCIS53392.2021.9754651 | 2021 IEEE 7th International Conference on Cloud Computing and Intelligent Systems (CCIS) |
Keywords | DocType | ISBN |
Training,Solid modeling,Conferences,Computational modeling,Collaboration,Collaborative work,Data models | Conference | 978-1-6654-4149-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haiyan Cui | 1 | 0 | 0.68 |
| Junping Du | 2 | 789 | 91.80 |
| Yang Jiang | 3 | 0 | 0.34 |
| Yue Wang | 4 | 486 | 38.99 |
| Runyu Yu | 5 | 0 | 0.34 |