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Learning models over relational data using sparse tensors and functional dependencies

Abstract:

Integrated solutions for analytics over relational databases are of great practical importance as they avoid the costly repeated loop data scientists have to deal with on a daily basis: select features from data residing in relational databases using feature extraction queries involving joins, projections, and aggregations; export the training dataset defined by such queries; convert this dataset into the format of an external learning tool; and train the desired model using this tool. The...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1145/3375661

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
College Only
Oxford college:
Kellogg College
Role:
Author
European Commission More from this funder
Publisher:
Association for Computing Machinery Publisher's website
Journal:
ACM Transactions on Database Systems Journal website
Volume:
45
Issue:
2
Article number:
7
Publication date:
2020-06-27
Acceptance date:
2019-12-01
DOI:
EISSN:
1557-4644
ISSN:
0362-5915
Language:
English
Keywords:
Pubs id:
1085366
Local pid:
pubs:1085366
Deposit date:
2020-02-06

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