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...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2015
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Online Access: | https://hdl.handle.net/10356/62213 |
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Institution: | Nanyang Technological University |
Language: | English |