Wasserman on Stats vs ML, and previous comparisons

Larry Wasserman has a new position paper (forthcoming 2013) with a great comparison the Statistics and Machine Learning research cultures, “Rise of the Machines”. He has a very conciliatory view in terms of intellectual content, and a very pro-ML take on the research cultures. Central to his argument is that ML has recently adopted rigorous statistical concepts, and the fast-moving conference culture (and heavy publishing by its grad students) have helped with this and other good innovations. (I agree with a comment from Sinead that he’s going a little easy on ML, but it’s certainly worth a read.)

There’s now a little history of “Statistics vs Machine Learning” position papers that this can be compared to. A classic is Leo Breiman (2001), “Statistical Modeling: The Two Cultures”, which isn’t exactly about stats vs. ML, but is about the focus on modeling vs algorithms, and maybe about description vs. prediction.

It’s been a while since I’ve looked at it, but I’ve also enjoyed Jerome Friedman (1998)’s “Data Mining and Statistics: What’s the Connection?” which looks at what I’d now consider a kind of dark ages, the heuristic data mining approaches I associate with the 90′s.

I think Larry in 2013 would argue that NIPS or ICML-style mainstream ML research has substantially moved away from the crazy heuristic world of data mining and into something that looks more like statistical theory. Larry’s obviously focusing on areas he’s interested in. For example, current work in deep belief networks feels much more heuristicky — some of us (like me) think this area is very important and are sympathetic to the approach, though plenty aren’t — but of course the combination of theory and creative algorithmic innovation is useful to have even when they haven’t yet been reconciled. That’s what you get if you want to follow bleeding-edge research.

It’s always interesting to read this sort of thing. Before going to grad school I wrote a blog rant about stats and ML; it’s nice to actually know something about the topic now. Or conversely, maybe my worldview has been sufficiently shaped by all of Larry’s classes that I think the same way. Whatever.

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