L1-regularized quadratic-surface SVMs are convex with unique generic solutions and provably reduce to standard SVMs on linearly separable data, but their advertised sparse-pattern recovery is not rigorously established.
Quadratickernel-freeleastsquaressupportvector machine for target diseases classification.Journal of Combinatorial Optimization, 30(4):850–870, 2015
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Quadratic Surface Support Vector Machine with L1 Norm Regularization
L1-regularized quadratic-surface SVMs are convex with unique generic solutions and provably reduce to standard SVMs on linearly separable data, but their advertised sparse-pattern recovery is not rigorously established.