Greedy Gaussian Segmentation of Multivariate Time Series

24 Oct 2016David HallacPeter NystrupStephen Boyd

We consider the problem of breaking a multivariate (vector) time series into segments over which the data is well explained as independent samples from a Gaussian distribution. We formulate this as a covariance-regularized maximum likelihood problem, which can be reduced to a combinatorial optimization problem of searching over the possible breakpoints, or segment boundaries... (read more)

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