Name
Title | ||
|---|---|---|
Communication and Computation Reduction for Split Learning using Asynchronous Training |
Abstract | ||
|---|---|---|
Split learning is a promising privacy-preserving distributed learning scheme that has low computation requirement at the edge device but has the disadvantage of high communication overhead between edge device and server. To reduce the communication overhead, this paper proposes a loss-based asynchronous training scheme that updates the client-side model less frequently and only sends/receives acti... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SiPS52927.2021.00022 | 2021 IEEE Workshop on Signal Processing Systems (SiPS) |
Keywords | DocType | ISSN |
Split learning,Communication reduction,Asynchronous training,Quantization | Conference | 1520-6130 |
ISBN | Citations | PageRank |
978-1-6654-0144-9 | 1 | 0.36 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xing Chen | 1 | 1 | 0.36 |
| Jingtao Li | 2 | 3 | 4.15 |
| Chaitali Chakrabarti | 3 | 1978 | 184.17 |