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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Functional regression on manifold with contaminati
 on - Fang Yao (University of Toronto\; University 
 of Toronto)
DTSTART;TZID=Europe/London:20180320T160000
DTEND;TZID=Europe/London:20180320T170000
UID:TALK102682AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/102682
DESCRIPTION:We propose a new perspective on functional regress
 ion with a predictor process via the concept of ma
 nifold that is intrinsically finite-dimensional an
 d embedded in an infinite-dimensional functional s
 pace\, where the predictor is contaminated with di
 screte/noisy measurements.  By a novel method of  
 functional local linear manifold smoothing\, we ac
 hieve a polynomial rate of convergence that adapts
  to the intrinsic manifold dimension and the level
  of sampling/noise contamination with a phase tran
 sition phenomenon depending on their interplay. Th
 is is in contrast to the logarithmic convergence r
 ate in the literature of functional nonparametric 
 regression. We demonstrate that the proposed metho
 d enjoys favorable finite sample performance relat
 ive to commonly used methods via simulated and rea
 l data examples. (Joint with Zhenhua Lin)  
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
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