Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27039
Title: Stock Predictor with Graph Laplacian-Based Multi-task Learning
Authors: He, J
Tran, NH
Khushi, M
Keywords: federated learning;multi-task learning;graph learning;stock prediction
Issue Date: 15-Jun-2022
Publisher: Springer Nature
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.
URI: https://bura.brunel.ac.uk/handle/2438/27039
DOI: https://doi.org/10.1007/978-3-031-08751-6_39
ISBN: 978-3-031-08750-9 (pbk)
978-3-031-08751-6 (ebk)
ISSN: 0302-9743
Other Identifiers: ORCID iD: Matloob Khushi https://orcid.org/0000-0001-7792-2327
Appears in Collections:Dept of Computer Science Research Papers

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FullText.pdfCopyright © 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 kBAdobe PDFView/Open


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