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Barnabás Póczos

 

Tuesday 9th June 2015

Time: 4.00pm

 

Basement Seminar Room

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

Machine Learning on Functional Data

In this presentation we discuss two novel results in functional data
analysis. i) We present FuSSO, a functional analogue to the LASSO,
which can efficiently find a sparse set of functional input covariates
to regress a real-valued response against. ii) We will also discuss a
new method for function-to-function regression, when both input
covariates and output responses are functions from a nonparametric
function class. We analyze the statistical properties of these methods
and demonstrate their performance in several real-world problems from
cosmology, computer vision, and neuroimaging.