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Random Forests are part of how the LHC found the higgs, based on my armchair understanding of the slide decks. Measurement, Monte Carlo and Machine Learning fo
by jasonwatkinspdx 11y ago
Random Forests are part of how the LHC found the higgs, based on my armchair understanding of the slide decks.
Measurement, Monte Carlo and Machine Learning form an interesting triangle. My impression of the LHC pipe is they used monte carlo model sims to train up classifiers that would flag the data relevant for distinguishing alternate models.
- ssantic 11y agoNot to hijack the thread, but would you mind posting a link to the LHC slide deck you mentioned?
- jasonwatkinspdx 11y agoI watched the announcement live stream. I'm sure the video and slides are up somewhere. Sorry I don't have it at hand.
- phreeza 11y agoThe major difference there is that LHC data measures processes which are inherently stochastic (because QM), so using these methods is pretty natural. The OP, however, is applying the same methods to highly complex, but nominally deterministic problems.
- noobermin 11y agoI'm curious about this. A lot of us in the computational world have to deal with able but slow iterative methods for things like fluid dynamics and electromagnetic simulations. I'd be interested to know if this works with MHD, and how well it does.
- phreeza 11y agoIt probably would, but it is harder to get performance guarantees. Seems like a taylor expansion on steroids, but with the taylor expansion you get analytical tractability (to prove correct convergence) along with speed, which you don't get in this case.