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Massive Data Classification via Unconstrained Support Vector Machines
A highly accurate algorithm, based on support vector machines formulated as linear programs [13, 1], is proposed here as a completely unconstrained minimization problem . Combined with a chunking procedure  this ...
Nonlinear Knowledge-Based Classification
Prior knowledge over general nonlinear sets is incorporated into nonlinear kernel classification problems as linear constraints in a linear program. The key tool in this incorporation is a theorem of the alternative for ...
Chunking for Massive Nonlinear Kernel Classification
A chunking procedure  utilized in  for linear classifiers is proposed here for nonlinear kernel classification of massive datasets. A highly accurate algorithm based on nonlinear support vector machines that ...
Nonlinear Knowledge in Kernel Approximation
Prior knowledge over arbitrary general sets is incorporated into nonlinear kernel approximation problems in the form of linear constraints in a linear program. The key tool in this incorporation is a theorem of the ...