GoGP: Fast online regression with Gaussian processes

Le, Trung, Nguyen, Khanh, Nguyen, Vu, Nguyen, Tu Dinh and Phung, Dinh 2017, GoGP: Fast online regression with Gaussian processes, in ICDM 2017 : Proceedings of the IEEE International Conference on Data Mining, IEEE, Piscataway, N.J., pp. 257-266, doi: 10.1109/ICDM.2017.35.

Attached Files
Name Description MIMEType Size Downloads

Title GoGP: Fast online regression with Gaussian processes
Author(s) Le, TrungORCID iD for Le, Trung orcid.org/0000-0002-7070-8093
Nguyen, Khanh
Nguyen, Vu
Nguyen, Tu Dinh
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Conference name IEEE Data Mining. International Conference (17th : 2017 : New Orleans, La.)
Conference location New Orleans, La.
Conference dates 2017/11/18 - 2017/11/21
Title of proceedings ICDM 2017 : Proceedings of the IEEE International Conference on Data Mining
Editor(s) Raghavan, Vijay
Publication date 2017
Start page 257
End page 266
Total pages 10
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science
PERCEPTRON
ISBN 9781538638347
ISSN 1550-4786
Language eng
DOI 10.1109/ICDM.2017.35
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2017 IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30108623

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 1 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 21 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Thu, 13 Sep 2018, 16:34:21 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.