My Ph.D thesis was titled "Distributed Machine Learning" and focused on boosted decision trees - this was 1997. Ok, I am small beer and I will get lost in any discussion with the smart folk at Cern in about 2 seconds flat, but I feel it necessary to say whenever I can that I was astonished when I read that the LHC was using a learned model over boosted decision trees as a noise filter. A large number of trees induced in data will find co-incidental outcomes; think about running trials - run 10 and the likelihood of a false positive is low, run 1000 and it's very high! Boost a decision tree and you will bring all sorts of things out of the margins; some of them will even be real. Is the bump in the higgs signal real? There were 15 events that generated that bump, out of n billion. What are the odds of a boosted tree regularizing the noise into that bin - I would say pretty decent.

But I am an old man, who knows little and does less. I shall return to my beer and vegetables.