【读论文】Multiple Kernel Learning, Conic Duality, and the SMO Algorithm（2004）

【读论文】Multiple Kernel Learning, Conic Duality, and the SMO Algorithm（2004）

多核学习、圆锥对偶和SMO算法

Francis R. Bach，Gert R. G. Lanckriet

DOI: 10.1145/1015330.1015424

摘要：

While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for the support vector machine (SVM),and showed that the optimization of the coefficients of such a combination reduces to a convex optimization problem known as a qu