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SUMMARY:Scaling Changepoint Detection to Big Data - Paul Fearnhead (Depart
ment of Maths and Statistics\, Lancaster University)
DTSTART;VALUE=DATE-TIME:20150611T141500
DTEND;VALUE=DATE-TIME:20150611T151500
UID:https://talks.ox.ac.uk/talks/id/056999e5-004a-4459-b532-5b27fb1fd604/
DESCRIPTION:Changepoint detection is an increasingly important problem in
a range of applications\, for example to detect copy number variants. A co
mmon approach to inferring the number and position of the changepoints is
to introduce a model for the data within a segment\, and then maximise a p
enalised likelihood function. This maximisation can often be done exactly
using dynamic programming\, but the resulting algorithm has a computationa
l cost that is quadratic\, or even cubic\, in the number of data points.\n
\nThis talk will cover some recent algorithms that can maximise the penali
sed likelihood function exactly\, but at a much lower computational cost.
This includes the first such algorithm that can be shown\, for certain mod
els\, to have an expected computational cost that is linear in the amount
of data.\nSpeakers:\nPaul Fearnhead (Department of Maths and Statistics\,
Lancaster University)
LOCATION:1 South Parks Road (Lecture Theatre)\, 1 South Parks Road OX1 3TG
URL:https://talks.ox.ac.uk/talks/id/056999e5-004a-4459-b532-5b27fb1fd604/
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DESCRIPTION:Talk:Scaling Changepoint Detection to Big Data - Paul Fearnhea
d (Department of Maths and Statistics\, Lancaster University)
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