To a large extent “ML” refers to a few particular technologies that have the form “try a bunch of things and do more of what works” or “consider a bunch of things and then do the one that is predicted to work.”
Why not “try a bunch of measurements and figure out which one generalizes best” or “consider a bunch of things and then do the one that is predicted to work according to the broadest variety of ML-generated measurements”? (I expect there’s already some research corresponding to these suggestions, but more could be valuable?)
Why not “try a bunch of measurements and figure out which one generalizes best” or “consider a bunch of things and then do the one that is predicted to work according to the broadest variety of ML-generated measurements”? (I expect there’s already some research corresponding to these suggestions, but more could be valuable?)