The maximum vector-angular margin classifier and its fast training on large datasets using a core vector machine

DOI10.1016/j.neunet.2011.10.005zbMath1250.68225OpenAlexW1983570277WikidataQ40005896 ScholiaQ40005896MaRDI QIDQ456027

Wenjun Hu, Fu-lai Chung, Shi-Tong Wang

Publication date: 23 October 2012

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2011.10.005

zbMATH Keywords

kernel methodscore vector machine (CVM)minimum enclosing ball (MEB)vector-angular margin

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (4)

A new semi-supervised classifier based on maximum vector-angular margin ⋮ Multi-view L2-SVM and its multi-view core vector machine ⋮ Scaling up minimum enclosing ball with total soft margin for training on large datasets ⋮ A core set based large vector-angular region and margin approach for novelty detection

Uses Software

• UCI-ml
• CVX
• LIBSVM
• FRSDE

Cites Work

• Unnamed Item
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• Support vector data description
• Support-vector networks
• FRSDE: Fast reduced set density estimator using minimal enclosing ball approximation
• Optimal core-sets for balls
• 10.1162/15324430260185619
• Training v-Support Vector Regression: Theory and Algorithms
• Approximate clustering via core-sets
• A Parallel Mixture of SVMs for Very Large Scale Problems
• Structural risk minimization over data-dependent hierarchies

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