Sparse and robust support vector machine with capped squared loss for large-scale pattern classification

Support vector machine (SVM), being considered one of the most efficient tools for classification, has received widespread attention in various fields. However, its performance is hindered when dealing with large-scale pattern classification tasks due to high memory requirements and running very slo...

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Veröffentlicht in:	Pattern recognition Jg. 153; S. 110544
Hauptverfasser:	Wang, Huajun, Zhang, Hongwei, Li, Wenqian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.09.2024
Schlagworte:	Capped squared loss Fast algorithm Low computational complexity Support vectors Working set Working set Fast algorithm Support vectors Capped squared loss Low computational complexity
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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