A simple decomposition algorithm for support vector machines with polynomial-time convergence

DOI10.1016/J.PATCOG.2006.12.024zbMath1120.68089OpenAlexW2093711054MaRDI QIDQ885211

Yan-Guo Wang, Hong Qiao, Bo Zhang

Publication date: 8 June 2007

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2006.12.024

zbMATH Keywords

convergencepattern recognitiondecomposition methodssupport vector machinesstatistical learning theory

Mathematics Subject Classification ID

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

Related Items (2)

Hierarchical mixing linear support vector machines for nonlinear classification ⋮ An online core vector machine with adaptive MEB adjustment

Uses Software

• SVMlight

Cites Work

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• Polynomial-time decomposition algorithms for support vector machines
• Downlink beamforming for DS-CDMA mobile radio with multimedia services
• Improvements to Platt's SMO Algorithm for SVM Classifier Design
• Learning Theory
• Convergence of a generalized SMO algorithm for SVM classifier design

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