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SUMMARY:The Sample Complexity of Multi-Reference Alignment - Philippe Rigo
llet\, (MIT Mathematics\, USA)
DTSTART;VALUE=DATE-TIME:20180622T143000Z
DTEND;VALUE=DATE-TIME:20180622T153000Z
UID:https://talks.ox.ac.uk/talks/id/5ecfa4a1-aefb-4b10-8b9e-7d057aa6fe3a/
DESCRIPTION:How should one estimate a signal\, given only access to noisy
versions of the signal corrupted by unknown cyclic shifts? This simple pro
blem has surprisingly broad applications\, in fields from aircraft radar i
maging to structural biology with the ultimate goal of understanding the s
ample complexity of Cryo-EM. We describe how this model can be viewed as a
multivariate Gaussian mixture model whose centers belong to an orbit of a
group of orthogonal transformations. This enables us to derive matching l
ower and upper bounds for the optimal rate of statistical estimation for t
he underlying signal. These bounds show a striking dependence on the signa
l-to-noise ratio of the problem. We also show how a tensor based method of
moments can solve the problem efficiently. Based on joint work with Afon
so Bandeira (NYU)\, Amelia Perry (MIT)\, Amit Singer (Princeton) and Jonat
han Weed (MIT).\nSpeakers:\nPhilippe Rigollet\, (MIT Mathematics\, USA)
LOCATION:Large Lecture Theatre
URL:https://talks.ox.ac.uk/talks/id/5ecfa4a1-aefb-4b10-8b9e-7d057aa6fe3a/
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DESCRIPTION:Talk:The Sample Complexity of Multi-Reference Alignment - Phil
ippe Rigollet\, (MIT Mathematics\, USA)
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