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DTSTART:20070311T020000
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DTSTAMP:20230328T093318
DTSTART;TZID=America/Detroit:20230320T160000
DTEND;TZID=America/Detroit:20230320T170000
SUMMARY:Workshop / Seminar:ISRMT: Improved very sparse matrix completing using an intentionally randomized \"asymmetric SVD\"
DESCRIPTION:Joint work with: Charles Bordenave (University Aix-Marseille)\nSimon Coste (Université de Paris P7\, LPSM) \n\nWe consider the matrix completion problem in the very sparse regime where\, on average\, a constant number of entries of the matrix are observed per row (or column). In this very sparse regime\, we cannot expect to have perfect recovery and the celebrated nuclear norm based matrix completion fails because the singular value decomposition (SVD) of the underlying very sparse matrix completely breaks down. \n\nWe demonstrate that it is indeed possible to reliably recover the matrix. The key idea is the use of a ``randomized asymmetric SVD'' (which we will define) to find informative singular vectors in this regime in a way that the SVD cannot. \n\nWe provide sharp theoretical analysis of the phenomenon\, including a prediction of the lower limits of statistical recovery and demonstrate the efficacy of the new method(s) using simulations.\n\nA recording of the talk can be found at http://leccap.engin.umich.edu/leccap/player/r/fDvGiW
UID:103553-21807465@events.umich.edu
URL:https://events.umich.edu/event/103553
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics,seminar
LOCATION:East Hall - EH 1866
CONTACT:
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