Label-sensitive task grouping by Bayesian nonparametric approach for multi-task multi-label learning

Zhang, Xiao, Li, Wenzhong, Nguyen, Vu, Zhuang, Fuzhen, Xiong, Hui and Lu, Sanglu 2018, Label-sensitive task grouping by Bayesian nonparametric approach for multi-task multi-label learning, in IJCAI 2018: Proceedings of the 27th International Joint Conference on Artificial Intelligence, International Joint Conferences on Artifical Intelligence, Vienna, Austria, pp. 3125-3131.

Attached Files
Name Description MIMEType Size Downloads

Title Label-sensitive task grouping by Bayesian nonparametric approach for multi-task multi-label learning
Author(s) Zhang, Xiao
Li, Wenzhong
Nguyen, Vu
Zhuang, Fuzhen
Xiong, Hui
Lu, Sanglu
Conference name Artificial Intelligence. International Joint Conference (27th : 2018 : Stockholm, Sweden)
Conference location Stockholm, Sweden
Conference dates 2018/07/13 - 2018/07/19
Title of proceedings IJCAI 2018: Proceedings of the 27th International Joint Conference on Artificial Intelligence
Editor(s) Lang, J.
Publication date 2018
Start page 3125
End page 3131
Total pages 7
Publisher International Joint Conferences on Artifical Intelligence
Place of publication Vienna, Austria
ISBN 9780999241127
ISSN 1045-0823
Language eng
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2018, International Joint Conferences on Artificial Intelligence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30120236

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 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 45 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Thu, 28 Mar 2019, 12:44:35 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.