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May 29, 2024 · Twin Parameter-margin support vector machine (TPMSVM) is a recent very powerful binary classifier. To improve its sparsity, a linear sparse ...
ABSTRACT. Twin Parameter-margin support vector machine (TPMSVM) is a recent very powerful binary classifier. To improve its sparsity, a linear sparse TPMSVM ...
Jun 1, 2024 · A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application to Vehicles Emissions. Chapter. Feb 2024. Renato De Leone ...
Joachims and Yu [16] proposed a cutting-plane subspace pursuit (CPSP) method for constructing a sparse SVM. The CPSP sparsity representation generates ...
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Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection.
Missing: twin | Show results with:twin
[PDF] Learning Optimally Sparse Support Vector Machines - CS.HUJI
www.cs.huji.ac.il › ~shais › papers
Abstract. We show how to train SVMs with an opti- mal guarantee on the number of support vec- tors (up to constants), and with sample com-.
Missing: twin | Show results with:twin
May 7, 2023 · The boundary is chosen in such a way that it maximizes the margin, which is the distance between the boundary and the closest data points from ...
This paper introduces a general Bayesian framework for obtaining sparse solutions to re- gression and classification tasks utilising models linear in the ...
Missing: twin | Show results with:twin
Oct 8, 2014 · [8–20]. For the standard SVM, the principal of maximizing the margin between two parallel support hyperplanes leads to solving a convex ...
A novel twin parametric-margin support vector machine (TPMSVM) for classification is proposed in this paper. This TPMSVM, in the spirit of the twin support ...