Apr 24, 2019 · This paper presents a L1-norm loss-based projection twin support vector machine (L1LPTSVM) for binary classification.
May 1, 2016 · This paper proposes a novel L1-norm loss based twin support vector machine (L1LTSVM) classifier for binary recognition.
This paper presents a L1-norm loss-based projection twin support vector machine (L1LPTSVM) for binary classification. In the pair of optimization problems ...
This paper proposes a novel L1-norm loss based twin support vector machine (L1LTSVM) classifier for binary recognition. In this L1LTSVM, each optimization ...
Bibliographic details on L1-norm loss-based projection twin support vector machine for binary classification.
To alleviate the sensitivity to outliers or the noise, we propose a capped L1-norm projection twin support vector machine (CPTSVM), where the L2-norm distance ...
[48] proposed a simple but effective robust discriminant analysis version based on the L 1 norm, which aims to maximize the inter-class dispersion. Panos et al.
The proposed NPTSVM seeks two optimal projection directions simultaneously by solving a single quadratic programming problem, and the projected samples of ...
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Mar 18, 2022 · TPMSVM is an efficient classifier but it losses the sparsity due to the weight vectors of the hyperplanes. To solve this issue, centroid-based ...
Feb 15, 2019 · This paper formulates a support vector machine with quantile hyper-spheres (QHSVM) for pattern classification. The idea of QHSVM is to build ...