PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Gaussian Processes for time-marked time-series data
John P. Cunningham, Zoubin Ghahramani and Carl Edward Rasmussen
In: AISTATS 2012(2012).

Abstract

In many settings, data is collected as multiple time series, where each recorded time series is an observation of some underlying dynamical process of interest. These observations are often time-marked with known event times, and one desires to do a range of standard analyses. When there is only one time marker, one simply aligns the observations temporally on that marker. When multiple time-markers are present and are at different times on different time series observations, these analyses are more difficult. We describe a Gaussian Process model for analyzing multiple time series with multiple time markings, and we test it on a variety of data.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:9632
Deposited By:Carl Edward Rasmussen
Deposited On:09 December 2012