Kernel projection algorithm for large-scale SVM problems.

DOI10.1007/BF02948824zbMath1057.68096MaRDI QIDQ1850682

Jue Wang, Jiaqi Wang, Qing Tao

Publication date: 2002

Published in: Journal of Computer Science and Technology (Search for Journal in Brave)

zbMATH Keywords

Support Vector Machinestatistical machine learningnearest point pair problem

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

A \(\nu \)-twin support vector machine (\(\nu \)-TSVM) classifier and its geometric algorithms ⋮ A general soft method for learning SVM classifiers with \(L_{1}\)-norm penalty ⋮ Kernel projection algorithm for large-scale SVM problems.

Cites Work

• Unnamed Item
• An iterative algorithm for finding a nearest pair of points in two convex subsets of \(\mathbb{R}^n\)
• Kernel projection algorithm for large-scale SVM problems.
• Finding the Point of a Polyhedron Closest to the Origin
• An Iterative Procedure for Computing the Minimum of a Quadratic Form on a Convex Set

This page was built for publication: Kernel projection algorithm for large-scale SVM problems.