Abstract
Original language | English |
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Pages (from-to) | 256-275 |
Number of pages | 20 |
Journal | Information Sciences |
Volume | 554 |
Early online date | 16 Dec 2020 |
DOIs | |
Publication status | Published - Apr 2021 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020
Funding
This work was supported in part by the National Natural Science Foundation of China (Grant 61772344, Grant 61811530324, Grant 61732011 and Grant 62076056), in part by the HD Video R&D Platform for Intelligent Analysis and Processing in Guangdong Engineering Technology Research Centre of Colleges and Universities (Grant GCZXA1409), in part by the Natural Science Foundation of Guangdong Province of China (Grant 2020B1515310008), in part by the Natural Science Foundation of Shenzhen (Grant JCYJ20170818091621856), in part by the Interdisciplinary Innovation Team of Shenzhen University, and in part by UKRI Future Leaders Fellowship (Grant No. MR/S017062/1) and Royal Society (Grant No. IEC/NSFC/170243).
Keywords
- Bayesian network
- Classifier chain
- Label correlation
- Multi-label learning
- Scoring function
- Topological sorting