Two new decomposition algorithms for training bound-constrained support vector machines

DOI10.1515/fcds-2015-0005zbMath1335.62105OpenAlexW1167044975MaRDI QIDQ275574

Lingfeng Niu, Yong Shi, Xi Zhao, Ruizhi Zhou

Publication date: 26 April 2016

Published in: Foundations of Computing and Decision Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/fcds-2015-0005

zbMATH Keywords

global convergencequadratic programmingsupport vector machinedecomposition algorithm

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Quadratic programming (90C20) Parallel algorithms in computer science (68W10)

Uses Software

• UCI-ml
• SVMlight
• OOQP
• GPDT

Cites Work

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• Pegasos: primal estimated sub-gradient solver for SVM
• Support-vector networks
• Sparse kernel SVMs via cutting-plane training
• Cutting-plane training of structural SVMs
• Optimization theory and methods. Nonlinear programming
• 10.1162/15324430152748218
• Object-oriented software for quadratic programming
• A simple decomposition method for support vector machines