[yorwba]

You should keep in mind that probably none of those machine-learning researchers has studied only math specific to that domain, so their papers are likely to include whatever math they have a background in, plus any new techniques they had to learn to get their results.

That said, everything I saw in the papers you linked was linear algebra, calculus or probability theory plus the usual smattering of background notation and set theory.

Once you have a solid background in those areas, it is likely more productive to look up the specific concepts mentioned in a paper (such as the Kullback-Leibler divergence or the Bellman equation), because by then you are probably too deep in the woods to find one resource that adequately covers all those different directions.