Slide: Summary of SVM  One of the kernel methods:  kernelization of linear large margin classifier.  Computation depends on Gram matrices of size .   Quadratic program:  No local optimum.  Many solvers are available.  Further efficient optimization methods are available (e.g. SMO, Plat 1999)  Sparse representation  The solution is written by a small number of support vectors.  Regularization  The objective function can be regarded as regularization with hinge loss function.  III-14
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