You are right, but the problem of a possible analogous "Machine Learning Theory" is that machine learning problems are highly nonlinear, and control theory has only been "solved" for linear problems. It we could solve nonlinear control that could immediately be applied to machine learning.
“Linear systems are important because we can solve them.” — Richard Feynman
Fair point. But of course the reasons for the nonlinearities are different. ML is not inherently nonlinear; ML is only nonlinear because linear neural nets are not very useful.
On the other hand linear control theory is quite useful for many real-world problems.
“Linear systems are important because we can solve them.” — Richard Feynman