If you’re a practitioner of machine learning, then there is little doubt you have seen or used an algorithm that falls into the general category of kernel methods. The premier example of such methods is the support vector machine. When introduced to these algorithms, one is taught that one must provide the algorithm with a kernel function that, intuitively, computes a degree of “similarity” between the objects you are classifying. In practice, one can get pretty far with only this under...
