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http://bura.brunel.ac.uk/handle/2438/23897Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Liu, Z | - |
| dc.contributor.author | Luo, X | - |
| dc.contributor.author | Wang, Z | - |
| dc.date.accessioned | 2022-01-07T13:32:16Z | - |
| dc.date.available | 2022-01-07T13:32:16Z | - |
| dc.date.issued | 2020-05-11 | - |
| dc.identifier.citation | Liu, Z., Luo, X. and Wang, Z. (2021) 'Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models', IEEE Transactions on Neural Networks and Learning Systems, 32 (4), pp. 1737 - 1749. doi: 10.1109/TNNLS.2020.2990990. | en_US |
| dc.identifier.issn | 2162-237X | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/23897 | - |
| dc.description.sponsorship | National Natural Science Foundation of China under grants 61772493 and 61933007; Natural Science Foundation of Chongqing (China) under grant cstc2019jcyjjqX0013; Pioneer Hundred Talents Program of Chinese Academy of Sciences. | en_US |
| dc.format.extent | 1737 - 1749 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | © 2020 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 | learning system | en_US |
| dc.subject | single latent factor-dependent non-negative and multiplicative update | en_US |
| dc.subject | non-negative latent factor analysis | en_US |
| dc.subject | neural networks | en_US |
| dc.subject | convergence | en_US |
| dc.subject | latent factor analysis | en_US |
| dc.subject | high-dimensional and sparse matrix | en_US |
| dc.subject | big data | en_US |
| dc.title | Convergence analysis of single latent factor-dependent, nonnegative, and multiplicative update-based nonnegative latent factor models | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1109/TNNLS.2020.2990990 | - |
| dc.relation.isPartOf | IEEE Transactions on Neural Networks and Learning Systems | - |
| pubs.issue | 4 | - |
| pubs.publication-status | Published | - |
| pubs.volume | 32 | - |
| dc.identifier.eissn | 2162-2388 | - |
| Appears in Collections: | Dept of Computer Science Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | © 2020 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. | 2.19 MB | Adobe PDF | View/Open |
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