Hi, I'm trying to study the [Graph Kernel](http://jmlr.csail.mit.edu/papers/volume11/vishwanathan10a/vishwanathan10a.pdf) paper, which describes ways to compute similarity measures between edge-labeled graphs.
Unfortunately, I'm an undergraduate, and while most of the mathematical background is known to me, some of it isn't. Specifically, the authors talk about so called __feature maps__. What are they and where do I learn about them? It looks like it is a concept from ML/AI, but I'm not sure. They also mention Hilbert Spaces and RKHS, but in a less pervasive way
Unfortunately, I'm an undergraduate, and while most of the mathematical background is known to me, some of it isn't. Specifically, the authors talk about so called __feature maps__. What are they and where do I learn about them? It looks like it is a concept from ML/AI, but I'm not sure. They also mention Hilbert Spaces and RKHS, but in a less pervasive way
