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Bayesian Online Changepoint Detection Ryan Prescott Adams
 

Summary: Bayesian Online Changepoint Detection
Ryan Prescott Adams
Cavendish Laboratory
Cambridge CB3 0HE
United Kingdom
David J.C. MacKay
Cavendish Laboratory
Cambridge CB3 0HE
United Kingdom
Abstract
Changepoints are abrupt variations in the
generative parameters of a data sequence.
Online detection of changepoints is useful in
modelling and prediction of time series in
application areas such as finance, biomet­
rics, and robotics. While frequentist meth­
ods have yielded online filtering and predic­
tion techniques, most Bayesian papers have
focused on the retrospective segmentation
problem. Here we examine the case where

  

Source: Adams, Ryan Prescott - Department of Electrical and Computer Engineering, University of Toronto

 

Collections: Computer Technologies and Information Sciences