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http://bura.brunel.ac.uk/handle/2438/27039Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | He, J | - |
| dc.contributor.author | Tran, NH | - |
| dc.contributor.author | Khushi, M | - |
| dc.coverage.spatial | London, United Kingdom | - |
| dc.date.accessioned | 2023-08-23T15:37:05Z | - |
| dc.date.available | 2023-08-23T15:37:05Z | - |
| dc.date.issued | 2022-06-15 | - |
| dc.identifier | ORCID iD: Matloob Khushi https://orcid.org/0000-0001-7792-2327 | - |
| dc.identifier.citation | He, J., Tran, N.H. and Khushi, M. (2022) 'Stock Predictor with Graph Laplacian-Based Multi-task Learning', in Groen, D. et al. (eds.) Computational Science – ICCS 2022. ICCS 2022. (Lecture Notes in Computer Science, vol 13350). Cham, Switzerland, Springer Nature, pp. 541 - 553. doi: 10.1007/978-3-031-08751-6_39. | en_US |
| dc.identifier.isbn | 978-3-031-08750-9 (pbk) | - |
| dc.identifier.isbn | 978-3-031-08751-6 (ebk) | - |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/27039 | - |
| dc.format.extent | 541 - 553 | - |
| dc.language | English | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.rights | Copyright © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. This is a pre-copyedited, author produced version of a book chapter accepted for publication in: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13350, following peer review. The final authenticated version is available online at https://doi.org/10.1007/978-3-031-08751-6_39 (see: https://www.springernature.com/gp/open-research/policies/book-policies). | - |
| dc.rights.uri | https://www.springernature.com/gp/open-research/policies/book-policies | - |
| dc.source | The International Conference on Computational Science ICCS 2022 | - |
| dc.source | The International Conference on Computational Science ICCS 2022 | - |
| dc.subject | federated learning | en_US |
| dc.subject | multi-task learning | en_US |
| dc.subject | graph learning | en_US |
| dc.subject | stock prediction | en_US |
| dc.title | Stock Predictor with Graph Laplacian-Based Multi-task Learning | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.doi | https://doi.org/10.1007/978-3-031-08751-6_39 | - |
| dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
| pubs.finish-date | 2022-06-23 | - |
| pubs.finish-date | 2022-06-23 | - |
| pubs.publication-status | Published | - |
| pubs.start-date | 2022-06-21 | - |
| pubs.start-date | 2022-06-21 | - |
| pubs.volume | 13350 LNCS | - |
| dc.identifier.eissn | 1611-3349 | - |
| dc.rights.holder | The Author(s), under exclusive license to Springer Nature Switzerland AG | - |
| Appears in Collections: | Dept of Computer Science Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. This is a pre-copyedited, author produced version of a book chapter accepted for publication in: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13350, following peer review. The final authenticated version is available online at https://doi.org/10.1007/978-3-031-08751-6_39 (see: https://www.springernature.com/gp/open-research/policies/book-policies). | 572.28 kB | Adobe PDF | View/Open |
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