Effective parallelisation for machine learning
We present a novel parallelisation scheme that simplifies the adaptation of learning algorithms to growing amounts of data as well as growing needs for accurate and confident predictions in critical applications. In contrast to other parallelisation techniques, it can be applied to a broad class of...
| Main Authors: | Kamp, Michael, Boley, Mario, Missura, Olana, Gärtner, Thomas |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
Massachusetts Institute of Technology Press
2017
|
| Online Access: | https://eprints.nottingham.ac.uk/48362/ |
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