Openly accessible

Efficient and effective accelerated higher-order logistic regression for large data quantities

Zaidi, Nayyar A., Petitjean, Francois and Webb, Geoffrey I. 2018, Efficient and effective accelerated higher-order logistic regression for large data quantities, in SDM2018 : Proceedings of the 2018 SIAM International Conference on Data Mining, SIAM, Philadelphia, Pa., pp. 459-467, doi: 10.1137/1.9781611975321.52.

Attached Files
Name Description MIMEType Size Downloads

Title Efficient and effective accelerated higher-order logistic regression for large data quantities
Author(s) Zaidi, Nayyar A.ORCID iD for Zaidi, Nayyar A. orcid.org/0000-0003-4024-2517
Petitjean, Francois
Webb, Geoffrey I.
Conference name SIAM Data Mining. Conference (2018 : San Diego, California)
Conference location San Diego, California
Conference dates 3-5 May. 2018
Title of proceedings SDM2018 : Proceedings of the 2018 SIAM International Conference on Data Mining
Editor(s) Ester, Martin
Pedreschi, Dino
Publication date 2018
Start page 459
End page 467
Total pages 9
Publisher SIAM
Place of publication Philadelphia, Pa.
Keyword(s) Higher-order Logistic Regression
Feature Engineering
Tuple/Feature Selection
SGD
Adaptive Step-Size
ISBN 1611975328
9781611975321
Language eng
DOI 10.1137/1.9781611975321.52
Indigenous content off
HERDC Research category E1.1 Full written paper - refereed
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30135392

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

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.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 58 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Tue, 03 Mar 2020, 14:45:57 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.