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SUMMARY:Fast algorithms for matrix completion and compressed sensing - Jar
 ed Tanner (University of Oxford)
DTSTART:20140612T140000Z
DTEND:20140612T150000Z
UID:TALK50582@talks.cam.ac.uk
CONTACT:Carola-Bibiane Schoenlieb
DESCRIPTION:Compressed sensing and matrix completion are techniques by whi
 ch simplicity in data can be exploited for more efficient data acquisition
 . For instance\, if a matrix is known to be (approximately) low rank then 
 it can be recovered from few of its entries. The design and analysis of co
 mputationally efficient algorithms for these problems has been extensively
  studies over the last 8 years. In this talk we present new algorithms tha
 t balances low per iteration complexity with fast asymptotic convergence\,
  allowing solutions to much larger problem sizes. These algorithms has bee
 n shown to have faster recovery time than any other known algorithm in the
  area\, both for small scale problems and massively parallel GPU implement
 ations. 
LOCATION:MR 14\, CMS
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