DRO

Large-scale online kernel learning with random feature reparameterization

Nguyen, Tu Dinh, Le, Trung Minh, Bui, Hung and Phung, Quoc-Dinh 2017, Large-scale online kernel learning with random feature reparameterization, in IJCAI 2017 : Proceedings of the 26th International Joint Conference on Artificial Intelligence 2017, [The Conference], [Melbourne, Vic.], pp. 2543-2549.

Attached Files
Name Description MIMEType Size Downloads

Title Large-scale online kernel learning with random feature reparameterization
Author(s) Nguyen, Tu DinhORCID iD for Nguyen, Tu Dinh orcid.org/0000-0002-7070-8093
Le, Trung MinhORCID iD for Le, Trung Minh orcid.org/0000-0002-7070-8093
Bui, Hung
Phung, Quoc-DinhORCID iD for Phung, Quoc-Dinh orcid.org/0000-0002-9977-8247
Conference name International Joint Conference on Artificial Intelligence (26th : 2017 : Melbourne, Victoria)
Conference location Melbourne, Victoria
Conference dates 2017/08/19 - 2017/08/25
Title of proceedings IJCAI 2017 : Proceedings of the 26th International Joint Conference on Artificial Intelligence 2017
Publication date 2017
Conference series International Joint Conference on Artificial Intelligence
Start page 2543
End page 2549
Total pages 7
Publisher [The Conference]
Place of publication [Melbourne, Vic.]
ISBN 9780999241103
ISSN 1045-0823
Language eng
HERDC Research category E1 Full written paper - refereed
Copyright notice ©[2017, The Conference]
Persistent URL http://hdl.handle.net/10536/DRO/DU:30104952

Document type: Conference Paper
Collection: Centre for Pattern Recognition and Data Analytics
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 3 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 78 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Fri, 17 Nov 2017, 20:07:38 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.