Compressed Support Vector Machines

26 Jan 2015Zhixiang XuJacob R. GardnerStephen TyreeKilian Q. Weinberger

Support vector machines (SVM) can classify data sets along highly non-linear decision boundaries because of the kernel-trick. This expressiveness comes at a price: During test-time, the SVM classifier needs to compute the kernel inner-product between a test sample and all support vectors... (read more)

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