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This paper considers the robust and efficient implementation of Gaussian process regression with a Student-t observation model. The challenge with the Student-t model is the analytically intractable i...
We consider the problem of online linear regression on indi- vidual sequences. The goal in this paper is for the forecaster to output sequential predictions which are, after T time rounds, almost as...
This paper considers the inference of regression functions in the context of multiple time series. For an arbitrary number of time series observed at a large number of time points, we test the hypoth...
We consider heteroscedastic nonparametric regression models, when both the mean function and variance function are unknown and to be estimated with nonparametric approaches. We derive convergence rate...

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