In some sense this is a crosspost of mine from math.stackexchange, and I have the feeling that this site might provide a broad audience.
I am looking for a mathematical introduction to machine learning. Particularly, lots of literature that can be found is relatively imprecise and a lot of pages are spent without any content.
However, starting from such literature, I discovered the Coursera courses from Andrew Ng, the book of Bishop on pattern recognition and finally a book of Smola. Unfortunately, the book of Smola is only in draft state. In Smola's book even proofs can be found, which appeals to me. Bishop's book is already quite good, but a certain amount of rigor is missing.
In short: I am looking for a book like Smola's, that is, as precise and rigorous as possible and uses mathematical background (though short introductions are of course OK).