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SUMMARY:Low-rank optimization: from differential geometry to recommender s
 ystems - Pierre-Antoine Absil (Louvain)
DTSTART:20140130T150000Z
DTEND:20140130T160000Z
UID:TALK49537@talks.cam.ac.uk
CONTACT:6743
DESCRIPTION:The central topic of this talk is low-rank optimization\, wher
 e the\narchetypal problem consists of minimizing a real-valued function\nd
 efined on a set of matrices of fixed or bounded rank. The fact that\nthe s
 et of fixed-rank matrices admits Riemannian manifold structures\nendows th
 e problem with rich geometry. We will see how geometric\nconcepts can be e
 xploited to design efficient low-rank optimization\nmethods\, and we will 
 show how low-rank optimization applies to\nrecommender systems. This talk 
 is based on joint work with Nicolas\nBoumal.
LOCATION:MR 14\, CMS
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