What a day! There were talks of various lengths by Valluri (Michigan), Thalmann (Amsterdam), Morganson, Bañados, Deacon, and Goldman (all MPIA). So much to report that I will report nothing except that PanSTARRS calibration is under control; it is only data access that needs work, and high-dynamic range imaging efforts at MPIA could benefit from the stuff Fergus and I are working on!
At lunch Finkbeiner (Harvard) showed up, and we discussed how to model the dust in the Milky Way in two (projected) and three dimensions. I showed him some technology to deal with the more parameters than data
non-problem, including regularizations that really only act when the data are failing to inform. I stuck with frequentist approaches, because we still don't understand how to do exceedingly enormous non-parameteric (think: infinitely parameterized) problems with full posterior output. There is a huge literature on this, so maybe one day we will have a breakthrough. I also stuck with methods that are fast, because if you want to build models with billions of parameters (and we do), you care.
I'm curious what the frequentist approaches were. Note that a point estimation procedure is not inherently frequentist -- it becomes so if you start evaluating its performance based on frequency properties.
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