Conference item icon

Conference item

In-database learning with sparse tensors

Abstract:

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 theoretically fundamental and challenging problems at the intersection of relational and statistical data models. This paper introduces a unified framework for training and evaluating a class of stat...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

Actions


Access Document


Files:
Publisher copy:
10.1145/3196959.3196960

Authors


Abo Khamis, M More by this author
More by this author
Department:
St Cross College
More by this author
Department:
Oxford, MPLS, Computer Science
Publisher:
Association for Computing Machinery Publisher's website
Pages:
325-340
Publication date:
2018-05-27
Acceptance date:
2017-09-01
DOI:
Pubs id:
pubs:725630
URN:
uri:2d852e0d-889d-46fe-890e-b1ac5687c798
UUID:
uuid:2d852e0d-889d-46fe-890e-b1ac5687c798
Local pid:
pubs:725630
ISBN:
978-1-4503-4706-8

Terms of use


Metrics



If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP