In-database learning with sparse tensors
In-database analytics is of great practical importance as it avoids the costly repeated loop data scientists have to deal with on a daily basis: select features, export the data, convert data format, train models using an external tool, reimport the parameters. It is also a fertile ground of theo...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Published: |
Association for Computing Machinery
2018
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