Kernel Trick, Support Vector Machine, Svm, Machine Learning, Data Science.
computing the kernel is easy, but computing the feature vector corresponding to the kernel is really really hard. The feature vector for even simple kernels can blow up in size, and for kernels like the RBF kernel (k(x,y) = exp( -||x-y||²), see Radial basis function kernel) the corresponding