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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:TALK102679AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/102679
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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