Distributed classification with variable distributions
When the data at a location is insufficient, one may apply a naive solution to gather data from other (remote) places and classify it using a centralized algorithm. Although this approach has good performance, it is often infeasible due to high communication overheads and lack of scalability of the...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2015
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/62213 |