Re:Are ML and Statistics Complementary? [pdf]
by murbard2 on Thursday December 31, 2015 @05:51PM
(#10820168)
It's not just a way to write them, it's a way to do inference. Probabilistic programming is extremely powerful in terms of representation but inference is, in general, intractable. Yes, you can express all those ML models as probabilistic programs, but the sampler isn't going to perform nearly as well as the original algorithm.
Probabilistic programming is already a hint of this. The most general class of probability distributions is that of non-deterministic programs. ML is just a quick and dirty way to write these programs.