Michael Hirsch (UCL & MPI-IS) arrived for two days at NYU. We talked about self-calibration and blind deconvolution. On the latter, I was arguing that many things people usually do in computer vision might not work for astronomy, because astronomers expect to be able to make measurements (especially flux measurements) on their processed images. Some computer vision methods break that, or make measurements highly biased. On that point, I did my usual disparage of non-negative. Like Schölkopf, Fergus disagreed: If we think the fundamental image-formation mechanism is non-negative, then non-negative is the way to go methodologically. I think there might be a problem if you impose non-negative but not, at the same time, other things that are similarly informative that you know about the imaging. Anyway, we left it that I would make a fake data set that obeys exactly the image formation model but still leads to badly biased results when standard blind deconvolution is applied to it. That would be a service to this endless argument.
We also thought more and argued more about the idea that Fadely's brain-dead model of tiny patches of SDSS imaging data could be used for self-calibration purposes. We have a rough plan, but we are still contemplating whether the calibration and the data model could be learned simultaneously.