Data Science, Kernel Trick, Machine Learning, Machine Learning Theory.
the loss minimizer, we don’t need to search the whole infinite dimensional space, but only the subspace spanned by the representers (a.k.a. Kₓ’s) of training data. What’s the magic behind this special inner product? How can we not consider the complement space to find the optimizer? The very most