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DC Field | Value | Language |
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dc.contributor.author | Huang, Y | - |
dc.contributor.author | Wang, Q | - |
dc.contributor.author | Yang, W | - |
dc.contributor.author | Liao, Q | - |
dc.contributor.author | Meng, H | - |
dc.date.accessioned | 2021-12-25T19:53:22Z | - |
dc.date.available | 2021-12-25T19:53:22Z | - |
dc.date.issued | 2021-12-21 | - |
dc.identifier.citation | Huang, Y., Wang, Q., Yang, W., Liao, Q. and Meng, H. (2021) 'Hierarchical Deep Multi-task Learning with Attention Mechanism for Similarity Learning,' IEEE Transactions on Cognitive and Developmental Systems, 0 (in press), pp. 1 - 15. doi: 10.1109/TCDS.2021.3137316. | en_US |
dc.identifier.issn | 2379-8920 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/23820 | - |
dc.description.sponsorship | Shenzhen Science and Technology Projects (Grant Number: JCYJ20200109143035495). | en_US |
dc.format.extent | 1 - 15 (15) | - |
dc.format.medium | Print-Electronic | - |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.rights | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | hierarchical learning | en_US |
dc.subject | multi-task | en_US |
dc.subject | graph similarity inference | en_US |
dc.title | Hierarchical Deep Multi-task Learning with Attention Mechanism for Similarity Learning | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1109/tcds.2021.3137316 | - |
dc.relation.isPartOf | IEEE Transactions on Cognitive and Developmental Systems | - |
pubs.publication-status | Published | - |
pubs.volume | 0 | - |
dc.identifier.eissn | 2379-8939 | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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FullText.pdf | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | 48.53 MB | Adobe PDF | View/Open |
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