Computer Science > Machine Learning
arXiv:2309.13960 (cs)
[Submitted on 25 Sep 2023]
Title:Newton Method-based Subspace Support Vector Data Description
View a PDF of the paper titled Newton Method-based Subspace Support Vector Data Description, by Fahad Sohrab and 2 other authors
View PDFAbstract:In this paper, we present an adaptation of Newton's method for the optimization of Subspace Support Vector Data Description (S-SVDD). The objective of S-SVDD is to map the original data to a subspace optimized for one-class classification, and the iterative optimization process of data mapping and description in S-SVDD relies on gradient descent. However, gradient descent only utilizes first-order information, which may lead to suboptimal results. To address this limitation, we leverage Newton's method to enhance data mapping and data description for an improved optimization of subspace learning-based one-class classification. By incorporating this auxiliary information, Newton's method offers a more efficient strategy for subspace learning in one-class classification as compared to gradient-based optimization. The paper discusses the limitations of gradient descent and the advantages of using Newton's method in subspace learning for one-class classification tasks. We provide both linear and nonlinear formulations of Newton's method-based optimization for S-SVDD. In our experiments, we explored both the minimization and maximization strategies of the objective. The results demonstrate that the proposed optimization strategy outperforms the gradient-based S-SVDD in most cases.
| Comments: | 8 pages, 2 figures, 2 tables, 1 Algorithm. Accepted at IEEE Symposium Series on Computational Intelligence 2023 |
| Subjects: | Machine Learning (cs.LG) |
| Cite as: | arXiv:2309.13960 [cs.LG] |
| (orarXiv:2309.13960v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2309.13960 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Newton Method-based Subspace Support Vector Data Description, by Fahad Sohrab and 2 other authors
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